diff --git a/README.md b/README.md
index 292153229d9754bc7a688dc4e2fcd0abe3ae60c4..808d4500871c86dc24cc43ec04d6dd8ad6ce9312 100755
--- a/README.md
+++ b/README.md
@@ -146,7 +146,7 @@ Then run:
 
 ```bash
 # distant main.nf file
-HOME="$ZEUSHOME/14985_loot/" ; nextflow run --modules ${MODULES} -hub pasteur gmillot/14985_loot -r v7.8.0 -c $HOME/nextflow.config ; HOME="/pasteur/appa/homes/gmillot/"
+HOME="$ZEUSHOME/14985_loot/" ; nextflow run --modules ${MODULES} -hub pasteur gmillot/14985_loot -r v7.9.0 -c $HOME/nextflow.config ; HOME="/pasteur/appa/homes/gmillot/"
 
 # local main.nf file ($HOME changed to allow the creation of .nextflow into /$ZEUSHOME/14985_loot/. See NFX_HOME in the nextflow soft script)
 HOME="$ZEUSHOME/14985_loot/" ; nextflow run --modules ${MODULES} main.nf ; HOME="/pasteur/appa/homes/gmillot/"
@@ -209,6 +209,11 @@ Gitlab developers
 
 ## WHAT'S NEW IN
 
+### v7.10.0
+
+1) Pointing to the singularity folder improved, new option "slurm_local" added better worflow report
+
+
 ### v7.9.0
 
 1) Pipeline improved
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/fastQC1/test.fastq2_trim_fastqc.zip b/example_of_result/20220120_res_CL14985_B4985_4_1645559065/fastQC1/test.fastq2_trim_fastqc.zip
deleted file mode 100644
index 6fb4f87f0d79e0d20bb61d5f90649b9518be8a6b..0000000000000000000000000000000000000000
Binary files a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/fastQC1/test.fastq2_trim_fastqc.zip and /dev/null differ
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/figures/plot_test.fastq2_insertion_hist_tot_zoom.png b/example_of_result/20220120_res_CL14985_B4985_4_1645559065/figures/plot_test.fastq2_insertion_hist_tot_zoom.png
deleted file mode 100644
index 25004752892e269924e3d9180ae9b0343a2a00b6..0000000000000000000000000000000000000000
Binary files a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/figures/plot_test.fastq2_insertion_hist_tot_zoom.png and /dev/null differ
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nf_trace.txt b/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nf_trace.txt
deleted file mode 100644
index c51b6ef8b9e8f3892d929ebed9e1cf8bf844523f..0000000000000000000000000000000000000000
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nf_trace.txt
+++ /dev/null
@@ -1,43 +0,0 @@
-task_id	hash	native_id	name	status	exit	submit	duration	realtime	%cpu	peak_rss	peak_vmem	rchar	wchar
-2	e7/424ee9	183	Nremove (1)	CACHED	0	2022-02-22 15:19:14.426	4.8s	1.7s	46.8%	12 MB	70.6 MB	16.8 MB	14.5 MB
-4	5c/9949b3	1152	trim (1)	CACHED	0	2022-02-22 15:19:19.373	12.3s	9.1s	42.9%	62.8 MB	5.6 GB	16.4 MB	12 MB
-7	1c/07097b	2902	kraken (1)	CACHED	0	2022-02-22 15:19:31.771	385ms	36ms	72.1%	0	0	150.8 KB	216 B
-6	71/e822e1	1618	fivep_filtering (1)	CACHED	0	2022-02-22 20:10:48.915	3s	1.6s	26.0%	9.6 MB	61.4 MB	28 MB	15.3 MB
-5	01/01ac2e	2923	fastqc1 (1)	CACHED	0	2022-02-22 15:19:31.867	20.3s	17.6s	76.6%	196.5 MB	3.1 GB	13.9 MB	1.2 MB
-8	74/0a40f9	2495	cutoff (1)	CACHED	0	2022-02-22 20:10:52.062	1.7s	632ms	19.5%	9.6 MB	61.3 MB	7 MB	3.9 MB
-10	d0/cf0991	8593	plot_fivep_filtering_stat (1)	CACHED	0	2022-02-22 15:21:47.464	16.9s	15s	63.1%	203.2 MB	2.4 GB	19.1 MB	816.6 KB
-9	7a/397d42	4382	fastqc2 (1)	CACHED	0	2022-02-22 20:27:19.170	6.3s	5s	61.3%	150.4 MB	3.1 GB	12.3 MB	1.2 MB
-11	91/8872f7	10025	bowtie2 (1)	CACHED	0	2022-02-22 20:40:59.028	4.2s	3.3s	58.6%	111.6 MB	239.5 MB	35 MB	16.2 MB
-12	9d/ad802f	271	motif	CACHED	0	2022-02-22 15:19:14.758	57.3s	54.4s	45.6%	235.2 MB	2.4 GB	48.3 MB	39.7 MB
-13	e7/0f8ca5	8799	plot_read_length (1)	CACHED	0	2022-02-22 20:40:42.125	16.9s	15.6s	67.1%	307.6 MB	2.5 GB	19.7 MB	717.5 KB
-17	70/4547a0	10486	Q20 (1)	CACHED	0	2022-02-22 20:41:03.310	1.6s	375ms	17.2%	5.8 MB	42.8 MB	3.2 MB	2.2 MB
-16	75/97cb47	10460	coverage (1)	CACHED	0	2022-02-22 20:41:03.292	2s	809ms	15.7%	5.1 MB	44.6 MB	479.7 KB	91 KB
-18	94/21967c	10518	multiQC	CACHED	0	2022-02-22 20:41:03.330	8.5s	8s	40.2%	70.9 MB	81.4 MB	28.3 MB	2.3 MB
-21	9b/c9d978	10927	no_soft_clipping (1)	CACHED	0	2022-02-22 20:41:04.907	1.5s	301ms	15.5%	3.4 MB	38.4 MB	2.1 MB	1.5 MB
-22	78/6a3590	11762	plot_coverage (1)	CACHED	0	2022-02-22 20:41:07.165	15.5s	14.7s	62.2%	203.7 MB	2.4 GB	19.1 MB	464.3 KB
-19	10/b42e02	11096	coverage (2)	CACHED	0	2022-02-22 20:41:05.307	1.8s	741ms	16.5%	5 MB	44.6 MB	335 KB	82.4 KB
-20	47/ef2076	10991	duplicate_removal (1)	CACHED	0	2022-02-22 20:41:04.940	2.9s	1.8s	25.5%	7.4 MB	53 MB	12.8 MB	6.6 MB
-23	1a/4b7041	12101	insertion (1)	CACHED	0	2022-02-22 20:41:08.884	1.4s	482ms	19.7%	9.1 MB	65.6 MB	2.5 MB	1.7 MB
-25	2b/d2a26d	13051	plot_coverage (2)	CACHED	0	2022-02-22 20:41:22.625	14.8s	14.1s	64.5%	206.5 MB	2.4 GB	19.1 MB	455.9 KB
-24	5e/1ca0b8	13773	coverage (3)	CACHED	0	2022-02-22 20:41:37.445	1.5s	578ms	19.7%	5.1 MB	44.6 MB	310.2 KB	82.1 KB
-27	f6/edb675	13925	seq_around_insertion (1)	CACHED	0	2022-02-22 20:41:38.925	6.3s	5.6s	72.5%	156.5 MB	2.3 GB	17.9 MB	229.4 KB
-26	9e/6e5dd6	14430	final_insertion_files (1)	CACHED	0	2022-02-22 20:41:45.265	6.5s	5.8s	72.1%	173.5 MB	2.3 GB	18 MB	266 KB
-28	55/2b9806	14883	plot_coverage (3)	CACHED	0	2022-02-22 20:41:51.764	15s	14.3s	63.9%	206.4 MB	2.4 GB	19.1 MB	459.1 KB
-29	ef/0f9c22	15606	extract_seq (1)	CACHED	0	2022-02-22 20:42:06.756	1.7s	840ms	19.6%	5.8 MB	50.2 MB	9.1 MB	4.5 MB
-34	93/91ac2a	15899	base_freq (1)	CACHED	0	2022-02-22 20:42:08.578	1.7s	91ms	13.5%	0	0	279.6 KB	16.8 KB
-33	9e/88bce3	15833	base_freq (4)	CACHED	0	2022-02-22 20:42:08.530	1.7s	102ms	11.5%	0	0	281.8 KB	19 KB
-32	dd/d59b9f	15868	base_freq (3)	CACHED	0	2022-02-22 20:42:08.560	1.4s	103ms	12.1%	0	0	282.4 KB	19.7 KB
-31	82/5592cb	15942	base_freq (2)	CACHED	0	2022-02-22 20:42:08.599	1.5s	97ms	11.6%	0	0	281.6 KB	18.9 KB
-30	ef/14c394	15793	random_insertion (1)	CACHED	0	2022-02-22 20:42:08.476	13.1s	12.1s	61.6%	384.1 MB	2.7 GB	30.7 MB	1.2 MB
-37	cb/7fbfc4	17176	logo (1)	CACHED	0	2022-02-22 20:42:21.604	9.6s	8.8s	61.0%	202.1 MB	2.4 GB	14.6 MB	873.7 KB
-40	53/74fd55	19631	global_logo	CACHED	0	2022-02-22 20:43:00.113	9.7s	9s	63.6%	203.3 MB	2.4 GB	14.6 MB	850.3 KB
-36	f6/b96d60	18408	logo (3)	CACHED	0	2022-02-22 20:42:40.654	9.6s	8.9s	61.1%	204.1 MB	2.4 GB	14.6 MB	882.6 KB
-35	54/42a221	19019	logo (4)	CACHED	0	2022-02-22 20:42:50.233	9.9s	9.2s	59.9%	206.5 MB	2.4 GB	14.6 MB	1002.2 KB
-38	13/c75c72	17797	logo (2)	CACHED	0	2022-02-22 20:42:31.183	9.5s	8.8s	61.4%	229.3 MB	2.4 GB	14.6 MB	852.9 KB
-41	b7/0ba328	20250	plot_insertion (1)	CACHED	0	2022-02-22 20:43:09.794	36.7s	36s	74.6%	998.8 MB	3.2 GB	40.3 MB	9.7 MB
-1	d1/d3302b	21389	init	COMPLETED	0	2022-02-22 20:44:27.767	1.8s	12ms	6.2%	0	0	104.1 KB	669 B
-3	6a/b7ac99	21417	report1	COMPLETED	0	2022-02-22 20:44:27.812	1.9s	18ms	6.0%	0	0	104.5 KB	683 B
-14	3f/736771	21506	backup	COMPLETED	0	2022-02-22 20:44:27.976	1.8s	13ms	6.1%	0	0	104.3 KB	518 B
-39	cb/a45b2e	21670	report2	COMPLETED	0	2022-02-22 20:44:28.329	1.5s	26ms	8.5%	0	0	130.8 KB	1.3 KB
-15	8d/8cfbe1	21537	workflowVersion	COMPLETED	0	2022-02-22 20:44:28.024	2s	637ms	12.5%	4.8 MB	38.4 MB	135 KB	1.7 KB
-42	41/e917b4	22159	print_report (1)	COMPLETED	0	2022-02-22 20:44:30.332	10.5s	9.7s	54.9%	243.9 MB	1 TB	31.2 MB	11.6 MB
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/fastQC1/test.fastq2_trim_fastqc.html b/example_of_result/20220120_test_1645716342/fastQC1/test.fastq2_trim_fastqc.html
similarity index 99%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/fastQC1/test.fastq2_trim_fastqc.html
rename to example_of_result/20220120_test_1645716342/fastQC1/test.fastq2_trim_fastqc.html
index 010cd0f8b56c5c28693a58b2144eade392010771..f8b3a5a0436c6ab1dee6fe35984e95cd3e54572c 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/fastQC1/test.fastq2_trim_fastqc.html
+++ b/example_of_result/20220120_test_1645716342/fastQC1/test.fastq2_trim_fastqc.html
@@ -184,4 +184,4 @@
   padding-top: 0;
   margin-top: 0;
   }
-</style></head><body><div class="header"><div id="header_title"><img src="data:image/png;base64,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" alt="FastQC"/>FastQC Report</div><div id="header_filename">Tue 22 Feb 2022<br/>test.fastq2_trim.fq</div></div><div class="summary"><h2>Summary</h2><ul><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M0">Basic Statistics</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M1">Per base sequence quality</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M2">Per tile sequence quality</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M3">Per sequence quality scores</a></li><li><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAEkklEQVR42s2XV2hUaxSF/4nRiaIoiKA+CDYMdsQnS8CAFREVsV4VUR9sWMECVuzYsETsGnvvivVaImhyU+Hq9VUfzKtKkptk5nz3rPkz42RyJskE5Xpgw8yZ8++1Zu+1yzGA+T8t8UPGJP1lTGquMenZxvwh02fd02+/jECOMSNdoEwX6KtrgQJjSv425rtMn3VPv+kZPfvTCLj/MM11WphnTNnnlJRA6fDhsGkTHDsG16/D2bOwfj3OtGmUDhjAZ78/oGd1RmcbTOBPY5JdRxmuo/IvyclBZ/lyeP8ePn6EoiLIyYE3b+D5c3j4EG7fhitXICMDZ8QIiv3+oM7Kh3wlRCDfmFbuwawiY0orOnWCmzfhwwcoLITsbMjKgmfP4MEDuHULLl+2kTh+PESAvXth7Voq+/RBPuRLPutFoOqfZ/1jzL8KK3l5UFAA797B69fw9Cncv29JXboEmZk2HYcOwZ49sG0bbNwIa9aAGzWnd2/kSz69IlGDgEIm1s6UKZCfD2/fwqtX8OQJ3LsHN27AxYtw5gwcPQoHDsDu3bB1K2zYAKtXw7JlsHAhzJ0LM2fipKaGI5FRK4EqwZVXtGtnc/viBTx+DHfvWsFduACnT8ORI7B/P+zaBVu2hETIqlUWeMECmDMHZsyASZNg3DgYNYrK1q2R71hhViMg5X4xJsjOnfDoEdy5A9euwfnzcOqUTUNurgXevBnWrYOVK2HJEli0yGpDaZk4EcaOhZFuNaanw6BB0KsXxT6fhFnoSUC1q/Jxhg61ir56Fc6dg5Mn4fBhq/jKSggE7GcBL14M8+bZUEsfwSCUl8OJEzBkCAwcCP37h8Dp1g2nZUuEEd0nov995iefLxASVKyiX76Eigoil4jouY4doUcPmyIRC18isW8fdO8OXbpA27bgguP388ltWMKqTsC2168lXbtWV/T27bBihRWdQKMvERI5kY0G16XvSllSkoWIsm+uCSvctkME1MfVShkzxipapSRFz54NzZtbR1J7LIlwSmLBVZrJyTXAZY4lEAjNjjABDRP1c6ZO/aHoCROgSZMfh+OR8AJv3NgTPGzCEmaEgCaahgrTp8PSpaAe0KhRzcMicfCgNwmBKx11gMuEJcyaBAQ8axa0aeN9WGFVbmPDHk6HNOHzJU4gkgKVYN++iYNHC1PirYNEjRREROi2TM/QxwPXd6/qkJDjkPAUYbgMv3kdUt7VjOKVmpcmRELd0sOfZxlGGpGi4BU2db2ysprgioxXdZSW2qEU6yclJU4jimrFwXi5C5OIBvcqUYGrjGNTOHgwTufO8VtxtWFUGwmlw6vJiIQmZCx4ixa2p7glXrUlFdY5jstrKyOP9hqx2Jx36ADz54fGdEV9xnH0QhKso5api2Ramu2q7qISdENfr4UkdiVrEIlWrex4Vim6Y9xxR3JCK1nsUlpeX2BX4dp8Qo1IE9XVQ2W/fokvpZ5ruSvMYLxQaycYPRp27Ij0BWfyZIqbNm34Wh7vxUQ1/L1ZM5z27aFnT0LTUwNs/HicYcMoce9pqfkpLya/zavZb/Ny+qvsPyB3ge/Rlc06AAAAAElFTkSuQmCC" alt="[FAIL]"/><a href="#M4">Per base sequence content</a></li><li><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAFlUlEQVR42s2XCUzTVxzHybIs0IgCLYqyQ9RtmhjCNKKbikajYVc22NThNjYjeC0yWBESxAV1Ckw8QEUF5ChnS4FyFETucwWU+7ClHKKiImLI4nCz9bv3/pS7ra1HtM1Lm/b/fp/ve+93PQMABq9y6D/Bz+ANNvethWxPw3Xs3wx/YAb9Tn6j/700AeZc1qccrhGPw2UNkk8Fx9voIceX9Tcz6Hf62/B/PPrsCxNgzjW043iyGjheRkOWQRzFt2IH/Nl4DDFyHjJ6siDoSoZ/YwB2VuyEffpGzA5iK+izdA6d+8wCyHa+SYyEsj2N/jU/aaL0vbIf0sF2tA92oOVBG+ruN6CqrwZldypR0FuMnBuXkX49C5GyaGwq3ASLU2ZKOpfaoLb0EmDibmLC8TQq5/iw/vlIaA1xjxiyQTmaH7Sitr8ekr5qlN6pQP6tImTfyIXoeiYEnSmIlSfiooyHc20R8G84htUZq0FtUFvUpk4ChldO4H6sRzvKXdEw0ISmgRZc7a/DXwRccrscebcKIb5xCWndGeB3CsGTJyBCGoPQtnCcajlLjugk/qgPxO+1h7Eqyw7UFrWpbiemCKBbRlW7lrmgcaAZV/prUXm3CsW3y3D5VgGyenKQ2p2OpM5k8NoTEC6Nxtm2MJxsPoPAxhM4XB+AA1cPwbvmADyqvPFLpQdsM1aodoIVqlUAdRp6bgv5HzBbXHFXgqLbpci9mY/MnmykdIuQ2CFATHs8wqRRONN6ASeaTyOg8TgO1fnDl4C9anzhLvHCnkp3uJTvgXOJC7YUOWN+0nww/jTJMSevvsHs+DRlSOsZFPaW4NLNPOLpYgi70pBAwFHtcbhwLRKnW8/jeHMIOecgHKw7iv1XD2Jf9X78KtmHyNZoiOQi/FiyHZsJ+Ov87/DZZUesEq8H+4SxkjLUCmDinISPY74jcm4Oe3RyVyriO/iIksUS8EWEtJ5DUFMwjhIH86s7Ap8rfvCs9oGbxBO7KtwQ3hKBrgdd6H94D3ypgIAdsD7nc6wWb8DyzDWYy58HyhifJ8ZWT5NMoLGCJ48jsZ2COHkSCSkezl+LQHBLKI40BGJLsRPW5qzDskxbLE5bDBuRDWwzV5DV2SGwNhCdAx0Yed172AdeWyyWpa/ColQbzE1+H7MTLcEOmKagrAkCaAqlWWwZf6kqlMY8+gDZ3jXZazEz0Rym8TPUDg+yetl9Kca/HikeIUUmgEXizAnPml2YDsoaSduMAJrHaSrdWvw9AYcR8LBHu0m4eJtvqRGsDS4k8DlJFlPnxM0AZVHmmABSTGg+31GxW+XRAfi51AWztKxaI/zxELNytXDVoCzKHBNAKhotKrsr9zIe7Vq+G5wEs9EJi1I+hFDKx7zkuTrAk7XCGQGERZlTBLiSuN1Ltn2BcMEEeGF3PoaI8dzObFgJ3nsuuHoBqiNwLNgMu+x1ow9SByrsyoNC+ZiBPFb8h5LrhWrhqTKhTnD1R6BywuWZn0zYejq2FTuj/k7tKEz5RPlccLVOOBKG7DATtZO+yXNATW81npD3ZHhaux5wTWE4kohoktA0cWPOelT3SkZFDMNT9ICbwCJplvpEND4Vm8ZqNrJBJWJIT7h5Ioek5a+wRLRUcyoeX4y0GaMiaEjqCn9X8A62le0ADXGLYLbmYjS+HJtGTdf5TLUNa5E1Kc8+8K09iPkJVk8vx+MbEm1H8bTBTjDFF3lfMlmVNipLREt0a0gmt2TPIsKKZEv3Ki5TU2gZt8+1168lm9yU6noc1MO3FDkxYNojhpH+YW2Gnf5Nqbq2nHHMWPVbbZNuA6firQghpZt2TRHSSGwn/eScYPNnb8s1XUxoDFtGWpD6sAgrxSvhSi4juypJ31f6ExwLSNsl/BicAOMXczF5ba5mr83l9GWN/wE1f784zfWjGwAAAABJRU5ErkJg" alt="[PASS]"/><a href="#M5">Per sequence GC content</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M6">Per base N content</a></li><li><img src="data:image/png;base64,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" alt="[WARNING]"/><a href="#M7">Sequence Length Distribution</a></li><li><img src="data:image/png;base64,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" alt="[FAIL]"/><a href="#M8">Sequence Duplication Levels</a></li><li><img src="data:image/png;base64,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" alt="[FAIL]"/><a href="#M9">Overrepresented sequences</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M10">Adapter Content</a></li></ul></div><div class="main"><div class="module"><h2 id="M0"><img src="data:image/png;base64,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" alt="[OK]"/>Basic Statistics</h2><table><thead><tr><th>Measure</th><th>Value</th></tr></thead><tbody><tr><td>Filename</td><td>test.fastq2_trim.fq</td></tr><tr><td>File type</td><td>Conventional base calls</td></tr><tr><td>Encoding</td><td>Sanger / Illumina 1.9</td></tr><tr><td>Total Sequences</td><td>8709</td></tr><tr><td>Sequences flagged as poor quality</td><td>0</td></tr><tr><td>Sequence length</td><td>30-175</td></tr><tr><td>%GC</td><td>54</td></tr></tbody></table></div><div class="module"><h2 id="M1"><img src="data:image/png;base64,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" alt="[OK]"/>Per base sequence quality</h2><p><img class="indented" 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AgsgUWhCCxLOaXR+116twCKwBJYcoFy98B6N5alnFKvzJ5r5RajCCyBJRcoAstSTilXti5q5RajCCyBRaHcObAekcaylFOWSuIVgm4xisASWHKBIrAEFiVbSW82bjGKwBJYcoFy98Da3VlayikzJbLBuMUoAktgUSgCS2BRgsozeMjTLUYRWAKLQrl7YEXO+FjKKVnX9XCLUQSWwKJQBJbAouxflt0tRhFYAksuUARWtpJoLEv5vZWnW4wisASWXKAILIFFaaO8D1y5xSgCS2DJBYrAqlISlzWylN9N+WwMbjGKwBo3sB6TiXxeYFEElsCifFGZve+NW4wisEYMrGk8TVtqGVsCiyKwvr78rTaWpfw+yvJCDG4xisA6xylCgUURWALLDsO9T6EIrK8F1l//9yPv4/9/Zn/kEhTK2sc/m2tSiT+YP0rGl7RWVt+796S/CyWopN9Y0C1GGVnpvSafI7CynoNlR04RWN9a/pYniSzlV1V2L87uFqMIrNEDa/eQlcCiCCyBRTlQib7vjVuMIrDGDazVY1QCiyKwhl3+Zq8js5RfSflc4MotRhFY5w6sZV0JLIrAGn/5m14JyVJ+FeWftHKLUQTWFQLrsRjPwaIIrLMsf+/GspRfQPkctXKLUQTWBZ/knnUldztyisAaYfn7717ZUn5aZfpcK7cYRWAJLIFFEVgCi1KlrF411C1GEVgCy46cIrAGWf6elvJzKVuvEHSLUQSWwBJYFIE10PL3T2NZys+gpC++4BajCCyBJbAoAmus5e/dWHYYoyrPyHWt3GIUgSWwBBZFYA23/OVdPMkO46jwdb9QBJbAElgUgXX6IyV2GOM8N86pWwpFYAksisASWHYYbS4A++eiVm4xisASWAKLIrCusfxF38DODqPDe0R6CyPK5ZXgVK7JcUVgyQWKwDpO8WTqMmVy8Knkw46ccnll+ZHqgdI1OUsRWHKBIrCOvhyAHUbs6efPyEv83GIUisASWBTKoIGVe2i9/niMHUbi6JRdLIUisAQWhXL6wCpYmK4aWInjRqdT7MgpAktgCSyKwLpXYCUa601nPbWoeCkPPFfp2e6Vd+HzfXaxFIrAElgUisAqXmQT5RRUgs/p3jwTl3/tqMyLcxZ8iV0shSKwBBaFIrBGfa1iurpavb3M/kEvOz8KRWAJLLlAEVjXCKwvXkDBzo9CEVgCSy5QBJbAolAoAktgCSyKwBJYFAqFIrAqA2t6AZ5lSG193o6cIrAEFoVCObUSvTifwCoIrGk8zVpq678FFkVgCSwKhXLDt2EWWOWnCD8htTxqJbAoAktgUSgUgSWwGgSWU4SUmwTWAW9iI7AoFIrAumlgbZ0uXDaWwKJcKbCOSR+BRaFQBNYdA2uZUOn/tSOn3DywDnhyqB0GhULp93byAuuIwFo9CSiwKALrdMfJ7JYoFBdQGGodu/tlGnafjyWwKAJLYFEoFIElsDIu0zCb4PWx7MgpAktgUSgUgSWwXMmdIrAElt0ShSKwBJbAkgsUgWW3RKFQBJbAkgsUgSWwKBSKwBJYAosisAQWhUIRWAJLYFEoAstuiUKhCCyBJRcoAktgUSgUgSWwBBZFYAksCoUisASWwKJQBJbdEoXS/+1lCt4m6xhFYAksuUARWAKLQnHUhyKwBBZFYAksCkVgSR+BJbAoFIFlF0uhCCyBJbDkAkVgCSwKRWBRBJbAoggsgUWhCCzpI7AEFkVgCSy7WApFYAksgSUXKALLLpZCEVgUgSUXKAJLYFEoAkv6CCyBRRFYAotCEVjSR2AJLApFYNnFUigCi3KGwJpedH+1pZafF1gUgSWwKN5eZrS3lxFYAmugwJrG01ZLCSyKwBJYFMr1Hi/SR2Add4pw1lLv/xVYFIElsCgUgSV9BFabwPr8t8CiCCyBRaEILOlTdr/kniC+YGCtHr4SWBSBJbAoFIElsFopBSv/uQNrq64EFkVgCSwKRWAJLIFVElhbz23feoGhwKIILIFFEVgCS2AJrJ3LNOxe9coRLIrAElgUisASWAIr4zINiSNVAosisAQWhSKwBJbAciV3CkVgyQXKTQOr66vVBJbAElgUisCSCxRvL0MRWAJLLlAElsCiCCxRIrAElsCiCCyBRRFYcoEisAQWRWAJLLlAEVgUgSWw5AJFYMkFSn/FE8MpAktgUSgCSy5QWipygSKwBBaFIrDkAkVgUQSWwJILFIElsCgCi0LJXPkzzlwLLLlAEVgCiyKwKJTmK7/AkgsUgSWwKAKLQhFYAosisAQWRWDJBYrAElgUisASJRSBRRFYAksuUASWwKIILIrAElgCiyKwBBZFYMkFisASWBSKwBIlFIFFEVgCSy5QBJZcoAgsisASWHbkFIElsCgCS5RQBNYssKYXRY18XmBRBJbAoggsuUARWKnAmsbTtKW2Pi+wKAJLYFEEllygCKy8U4TLg1WrnxdYFIElsCgCSy5QBJbAoggsgSVKrq/E3yJXLlAE1nGBFawrgUURWAKLMqBiR04RWCMGVryuBBZFYAksisCiUATWfmBl1ZXAoggsgUURWBSKwNq/TENWXQksisASWBSBRaEIrJ3LNMwm/XmBRRFYAosisCgUgeVK7hSBJbBEicCSCxSBJbDkAkVgyQWKwKIILIFlR04RWAKLIrAoFIElsCgCS2BRBJZcoAgsgUWhCCxRQhFYFIElsOQCRWAJLIrAolAElsCiCCyBRRFYcoEisAQWhSKwRAnFjpwisASWXKAILIFFEVgUgSWwBBZFYAksisCSCxSBJbAoFIElSgSWHTlFYAksuUARWFuBFRxRQrEjpwgsgSUXKAKrlyJKBJYdOUVgCSy5QBFYAosisCgCS2AJLIrAElgUgUWhCCyBRaEILFEisDxeKAJLYMkFisASWBSBRRFYAsuOnCKwBBZFYFEoAktgUQSWwBIlAsvjhSKw+gbW9Go6kc8LLIrAElgUgUWhCKxUYE3jadZSn/8WWBSBJbCkj8CiUARW+SnCraha/q8dOUVgCSyKwKJQBFbrwPrxI+/j58/sj1yCQln7+GdzzVRSW/jYSsZe+beS8SWUsZUrbcmUCyttV/5zBNbq+UGBRRFYAkv6CCwKRWAVBtZuUQksisASWBSBRaEIrIzAWn0au8CiCCyBJX0EllygCKzyyzRkPR9LYFEElsCiCCwKRWDtXKZhNtHrYNmRUwSWwKIILApFYDW+krsdOUVgCSyKwKJQBJbAoggsgSVKBJbHC0VgCSy5QBFYAosisCgCS2DJBYrAElgUgUWhCCyBRRFYAkv6CCy5QBFYAotCsfwJrFsowbEjpwgsgSUXKAJLYFFCih05RWAJLDtyisASWBSBRaEILIFFEVgCS/oILApFYAksCkVgCSyBZUdOEVgCSy5QBJbAoggsCkVgCSyKwBJY0kdgUSgCS2BRKJY/gSWw7MgpAktgyQWKwBJYFIFFEVgCS2BRBJbAkj4Ci0IRWAKLQhFY0kdg2ZFTBJbAkgsUgSWwKAKLIrAElsCiCCyBRRFYFIrASgTW5+1CVytq608FFkVgCSyKwKJQBNbOEazVhEr/rx05RWAJLIrAolAElsCiCCyBJX0ElscLRWAJLLlAEVgC6ypKcGzJFIF18cDyHCyKwBJYAquVYhdLoQgsR7AoAktgCSyBRaEILIFFoVj+pI/AolAElsCSCxSBJbAEli2ZIrBucR2s5XOtPAeLIrAElsASWBSKwHIldwpFYEkfgUWhdFxh6l8PK7AEFkVgCSyBJbAolKFXfoElFygCS2AJLDtyisASWAKLIrAElsASWBSKwBJYFIrlT/oILApFYAksuUARWAJLYNmSKQJLYAksisASWBSBRaEILIFFoQgs6SOwKBSBJbDkAqVKybhMi8CSPgKLQhFYAotCOUwRWAJLYFEoAktgUSgCS/oILApFYAksO3KKwBJYAsuOnCKwBJbAoggsgUURWBSKwBJYFIrAkj4Ci0IRWAJLLlAElsASWHbkFIElsOzIKQJLYFEEFkVgCSyBRaEILOkjsCgUgSWwKBSBJbAElh05RWAJLDtyisASWBSBRRFYdw+sz9uGbIXU6p8KLIrAElgUgUWhCKydI1irgTX95OwvCCyKwBJYFIFFoQis7MDaOqYlsCgCS2BRBBaFIrCqAsspQorAElgCS2BRKAKrZWB9PrlsLIFFEVgCiyKwKBSBVXuKUGBRBJbAoggsCkVgCSwKRWBJH4FFoQisgV9F6BQhRWAJLIElsCgUgVVyHazVivIkd4rAElgCS2BRKALLldwpFIElfQQWhSKwBJZcoAgsgSWw7MgpAktgCSyKwBJYFIFFoQgsgUWhCCzpI7AoFIElsOQCRWAJLIFlR04RWALLjpwisAQWRWBRBJbAElgUisCSPgKLQhFYAotCEVgCS2DJBYrAElh25BSBJbAoduQUgSWwBBaFIrAElsCiUASWwKJQBJbAOlwJjh05RWAJLIFFoQgsgRVS7GIpFIElsCgUgSWwBBaFIrAEllygCCyBdawSPd9nF0uhCCyBRaEILIHl6ecUisASWHKBIrAElsCiUASWwLIjpwgsgSWw7GIpAktgCSwKRWAJLIFFoQisIwLr8/zNREst/1RgUQSWwBJYdrEUisDaOYIlsCgUgSWw7GIpFIF1UGC9Py+wKAJLYAksu1gKRWC1CazPJwUWRWAJLIFlF0uhCCyBRaEILIElsCgUgTVeYE0/I7AoAktgCSy7WApFYLUJrNkILIrAElgCyy6WQhFYbV5F6AgWRWAJLIFlF0uhCKzC62AlroYlsCgCS2AJLLtYCkVguZI7hSKwBJbAolAElsCSCxSBJbAEFoUisASWHTlFYAksgWUXSxFYAktgUSgCS2AJLApFYAksuUARWAJLYFEoAktg2ZFTBJbAElh25BSBJbAEFoUisASWXSyFIrAEFoUisASWwKJQBJbAsiOnCCyBJbAoFIElsAQWRWAJLIFlF0uhCCyBRaFUKI/wCCyBZRdLoQgsgUWhHKcILIFlR04RWAJLYFEoAktg2cVSKAJLYFEoJw+sY05ECiyBRaEILIFlR0659RGsThknsAQWhSKwBJYdOUVgCSyBRaEILIElsCgUgVWkRM+QHqvYxVIoAktgUSgC66yBdczvYudHoQisUQLr8++51Yra+lOBRaEILIFFoVAE1s4RrNWEmpWWwKJQBJbAolAoAqsqsNJ/QWBRKAJLYFEoFIElsCgUgSWw7GIpFIE1UmB5DhaFIrAEFoVCEVgtA2vr+e92sRSKwBJYFIrAElglgZX4vF0shSKwBBaFcl6lyXXjBFZJYKUPa9nFUigCS2BRKFdSzrgmn+A6WLNrMSwDVmBRKAJLYFEoAktguZI7hSKwBJZdLIUisASWHTlFYAksgUWhCCyBZRdLoQgsgUWhCCyBJbAoFIElsOxiKRSBJbAoFIElsAQWhSKwBJYdOUVgCSyBRaEILIElsCgUgSWw7GIpAktgCSwKRWAJLIFFoQgsgWVHTrmScsxbTBQoGV9yrFIWWAcox+z8hr1fKHdWBJbAolAooyuOLtjGKBSBJbAoFIrAElgUisASWBQKRWAJLFsyhSKwbDQUisASWLYxCkVgCSwKhSKwBBaFIrAEFoVCEVgCi0IRWALLRkOhCCyBZRujUASWwKJQKALrO1dBs41RKALLRkOhCCzXv7aNUSgCS2BRKBSBJbAoFIHVL7A+h7JXK2rrTwUWhXJn5eZvYmMbo1AEVvQI1lZgbf2pwKJQKJWKp59TKJQ7BtbsM8v/tdFQKBSB5d6nUASWwKJQKF9TCl55V3Dyzuv7KBSBJbBsNBQKhUKhUASWwKJQKBQKhSKwBBaFQqFQKBSB5VWENhoKhUKhUCgXug7W8npXroNFoVAoFApFYLmSO4VCoVAoFIElsGw0FAqFQqFQBJbAolAoFAqFIrAEFoVCoVAoFIElsGw0FAqFQqFQBJaNhkKhUCgUisASWBQKhUKhUASWwKJQKBQKhUIRWDYaCoVCoVAoAktgUSgUCoVCEVgCi0KhUCgUisASWDYaCoVCoVAoAktgUSgUCoVCEVgCi0KhUCgUisASWDYaCoVCoVAoAktgUSgUCoVCEVgCi0KhUCgUisASWDYaCoVCoVAoJw6sx2QEFoVCoVAoFIFVG1izqAo2lsCiUCgUCoUisAQWhUKhUCgUgSWwbJoUCoVCoVA8B8tGQ6FQKBQKRWA5gkWhUCgUCkVgCSwKhUKhUCgUgWWjoVAoFAqF4jlYnoNFoVAoFApFYLmSO4VCoVAoFIElsGw0FAqFQqFQBJbAolAoFAqFIrAEFoVCoVAoFIElsGw0FAqFQqFQBJaNhkKhUCgUisASWBQKhUKhUASWwKJQKBQKhUIRWDYaCoVCoVAoAktgUSgUCoVCEVgCi0KhUCgUCkVg2WgoFAqFQqEILIFFoVAoFApFYAksCoVCoVAoAktg2WgoFAqFQqEILIFFoVAoFApFYAksCoVCoVAoAktg2WgoFAqFQqFcJbAev0dgUSgUCoVCEVgNAmvaVcHGElgUCoVCoVAE1mZgxY9aCSwKhUKhUCgCKyOwnCKkUCgUCoUisFoG1qer4o0lsCgUCoVCoQis6ClCgUWhUCgUCkVgCSwKhUKhUCgCa+BXETpFSKFQKBQKRWA1CyxPcqdQKBQKhSKwXMmdQqFQKBSKwBJYNhoKhUKhUCgCS2BRKBQKhUIRWAKLQqFQKBSKwBJYNhoKhUKhUCgCS2BRKBQKhUIRWAKLQqFQKBSKwBJYNhoKhUKhUCgCy0ZDoVAoFApFYAksCoVCoVAoAktgUSgUCoVCoQgsGw2FQqFQKBSBJbAoFAqFQqEILIFFoVAoFApFYAksGw2FQqFQKBSBJbAoFAqFQqEILIFFoVAoFApFYAksGw2FQqFQKBSBJbAoFAqFQqEIrEBgPf4dgUWhUCgUCkVgCSwKhUKhUCgCa8jAeqeVwKJQKBQKhSKw2gTWp6sEFoVCoVAoFIElsCgUCoVCoQis8QJrGlUCi0KhUCgUisBqE1izEVgUCoVCoVAEVrPrYDmCRaFQKBQKRWAJLAqFQqFQKALLldxtNBQKhUKhUASWwKJQKBQKhSKwBBaFQqFQKBSBJbBsNBQKhUKhUASWwKJQKBQKhSKwBBaFQqFQKBSBJbBsmhQKhUKhUASWjYZCoVAoFIrAElgUCoVCoVAElsCiUCgUCoVCEVg2GgqFQqFQKAJLYFEoFAqFQhFYAotCoVAoFIrAElg2GgqFQqFQKAJLYFEoFAqFQhFYAotCoVAoFIrAElg2GgqFQqFQKALLRkOhUCgUCkVgbQTWYzICi0KhUCgUisCqDaxpVMUbS2BRKBQKhUIRWNFThAKLQqFQKBSKwBJYFAqFQqFQBNbAgeU5WBQKhUKhUARWy8CK15XAolAoFAqFIrD2AyurrgQWhUKhUCgUgbV/mQbXwaJQKBQKhSKwWl6mYTYCi0KhUCgUisByJXcKhUKhUCgCS2DZaCgUCoVCoQgsgUWhUCgUCkVgCSwKhUKhUCgCS2DZaCgUCoVCoQgsGw2FQqFQKBSBJbAoFAqFQqEILIFFoVAoFAqFIrBsNBQKhUKhUASWwKJQKBQKhSKwBBaFQqFQKBSKwLLRUCgUCoVCEVgCi0KhUCgUisASWBQKhUKhUASWwLLRUCgUCoVCEVgCi0KhUCgUisASWBQKhUKhUASWwLLRUCgUCoVCuUJgPSYjsCgUCoVCoQisNoE1+w+BRaFQKBQKRWCVB9YsqoKNJbAoFAqFQqEIrPaBZYwxxhhzw+kYWMYYY4wxRmAZY4wxxggsY4wxxpiTBtar6FWExhhjjDFmJ7Byr4NljDHGGGNSgdXg2xX1WdkFTmusXCJLyfqSrJckfPEWW35V5MdO/GmTmt/6JpFvnv47Tf6ZMfsmWXd02S9VfIdGXxTT5xbbehRkbWPLv3aBbSz3EdTpUdn2lrz271L82M/9nsf8Ls3vl8ol6NaB9bmlyv5y8MatebpYVsRU/u4F36HTrz/baTW5T7ParvnPk74ddr/57m3YKbAq46zyFktsn5Fvnv5dGq6MNb/pLM7qt7GtbxLZxtJ/p3ItWv3mNY/KxPds+OyR9EpSZmV9z66/S/1jPzfauv4uuUtEzfe85DOUvh9Y9V+be3/3C6z6QwuVYdEjSTsFVsPbLf34L759mtybNYts4mtbVXL8m+8e2Wp+PxZ8w963WNY2lv47lWtRbu01/J69V7lWO/Iv/i71j/3D1oSCFb7hNtZ1jyCwDs2a3Mdt2Zm7V+l50jMGVvy80okCq+2BooJThJEjEzW5sHrMP5gLW8f2e9yPBY/BswRWwVoU/8GaPyq/GFjFv8sXA6vmsf+qOFrZKbDKThEWfE+B1T2w+j3V6VV93qHgTFzxqdKs+Mv9+XvEX7AYGv48ic0g/ljtlwtZ54/iC3TlLRY8V7J7PmvrBj/ynEskaC5zi5X9E6XgUZkInSaP1lfsUGj975JO9q6/S81j/1Vx6rZHYO1+/1Yrf9vfRWAdnWWVT4064EBR8XHX3ANynQ4TLv/dGVn9e5xa2v3Hfdk/EIuPwWTdYulSrLzFcg9RJMS2t1junjJdxm23sdVvEtzGdr+2a2DlPirTh9xaPVrrOym4wnTdKiK3Ye5jv+B7Hva7nGsbE1jN6uqV8yzvmtcpdA2smhQ75taOB1bbr20YWFlrd83rWYLfZPelT7lf2zyw4oc3Wr2ayTbWaed3zPesuZd73Pu9t4rdJ060ul/6rQmX3MYEVsu/34kreHnja+O4+tcDq8cBvPjtU/zvvOLbof5VhK/OT9kOvkS/7S2W2D6zXkW4eyCw0/GA725jBa8ibLUjKTvs2vBUVMMHRXzLafW7NN8qcg+51f8uXdeE4Pawe5qy4fd8XWV6XQdrwAtBlR1YOuByU8XPCSv7wRrep7nXKGry80R+gPprFPUIrNw77la3WGQTKv7aJrdY2Q9Wszcte/Q1eVT23vYST5rOupJZzffsvadreL8ctiacfRu7xREsY4wxxpg7j8AyxhhjjBFYxhhjjDECyxhjjDFGYBljjDHGGIFljDHGGCOwjDHGGGMEljHGGGOMEVjGGGOMMQLLGGOMMUZgGWPMhRbE5Ft/pP9O4nte7A1AjDECyxizvr+vfOevrdro8QaOgwRWzY8nsIwRWMaY6wdWw33/1d6cVWAZYwSWMaZtYMXf6P7938u/v/vdZl+Y/gnjf3n2M6R/i8TnV5Xg309/H41ljMAyxtwxsJaNstpMW/8R/267R4Ny//KyctK/ReTn3A2srF9TYBkjsIwx1w+sxLGlREtF/rT48/V/Of4lnYiyn8QYI7CMMRcJrMjnV09+nSKwsk7hCSxjjMAyxnwnsBIxMfgRrMoqEljGGIFljKkNrGOeg9U7sHaPtMWfOLWqFDwHS10ZI7CMMTcNrFf+qwiXfxR8FWG/wAr+FvFX/6V/r+D3EVjGCCxjjDHr6VlWrq7kbozAMsYYUx5hbgRjjMAyxhiBZYwRWMYYY4wxAssYY4wx5p7zH5y/5IZ1CKiKAAAAAElFTkSuQmCC" alt="Per base quality graph" width="800" height="600"/></p></div><div class="module"><h2 id="M2"><img src="data:image/png;base64,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" alt="[OK]"/>Per tile sequence quality</h2><p><img class="indented" src="data:image/png;base64,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" alt="Per base quality graph" width="800" height="600"/></p></div><div class="module"><h2 id="M3"><img src="data:image/png;base64,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" alt="[OK]"/>Per sequence quality scores</h2><p><img class="indented" 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" alt="Per Sequence quality graph" width="800" height="600"/></p></div><div class="module"><h2 id="M4"><img src="data:image/png;base64,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" alt="[FAIL]"/>Per base sequence content</h2><p><img class="indented" src="data:image/png;base64,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" alt="Per base sequence content" width="800" height="600"/></p></div><div class="module"><h2 id="M5"><img src="data:image/png;base64,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" alt="[OK]"/>Per sequence GC content</h2><p><img class="indented" src="data:image/png;base64,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" alt="Per sequence GC content graph" width="800" height="600"/></p></div><div class="module"><h2 id="M6"><img src="data:image/png;base64,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" alt="[OK]"/>Per base N content</h2><p><img class="indented" 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kKhUCgUisASWBQKhUKhUASWwKJQKBQKhUIRWA4NhUKhUCgUgSWwKBQKhUKhCCyBRaFQKBQKhSKwHBoKhUKhUCgCS2BRKBQKhUIRWAKLQqFQKBSKwBJYDg2FQqFQKBSBJbAoFAqFQqEILIFFoVAoFApFYAksh4ZCoVAoFIrAcmgoFAqFQqEILIFFoVAoFApFYAksCoVCoVAoFIHl0FAoFAqFQhFYAotCoVAoFIrAElgUCoVCoVAElsByaCgUCoVCoQgsgUWhUCgUCkVgCSwKhUKhUCgCS2A5NBQKhUKhUASWwKJQKBQKhSKwBBaFQqFQKBSBJbAcGgqFQqFQKALLoaFQKBQKhSKwBBaFQqFQKBSBJbAoFAqFQqFQBJZDQ6FQKBQK5UUCa/rv1k9ZP11gUSgUCoVCEVjtgVWbTQKLQqFQKBSKwHoTRvd5tBdbAotCoVAoFIrAOg6szStVbYF1MzMzM7v0HhBYrmBRKBQKhUJxBWs3qgQWhUKhUCgUgdUeWIsJLAqFQqFQKAKr92uwDq9a+S5CCoVCoVAoAistsPwcLAqFQqFQKAKrK7ASbldgUSgUCoVCEVgCi0KhUCgUisASWI4mhUKhUCgUgeXQUCgUCoVCEVgCi0KhUCgUisASWBQKhUKhUCgCy6GhUCgUCoUisAQWhUKhUCgUgSWwKBQKhUKhCCyB5dBQKBQKhUIRWAKLQqFQKBSKwBJYFAqFQqFQBJbAcmgoFAqFQqEILIeGQqFQKBSKwBJYFAqFQqFQBJbAolAoFAqFQhFYDg2FQqFQKBSBJbAoFAqFQqEILIFFoVAoFAqFIrAcGgqFQqFQKAJLYFEoFAqFQhFYAotCoVAoFIrAElgODYVCoVAoFIElsCgUCoVCoQgsgUWhUCgUCkVgCSyHhkKhUCgUisByaCgUCoVCoQgsgUWhUCgUCkVgCSwKhUKhUCgUgeXQUCgUCoVCEVgCi0KhUCgUisASWBQKhUKhUASWwHJoKBQKhUKhCCyBRaFQKBQKRWAJLAqFQqFQKAJLYDk0FAqFQqFQBJbAolAoFAqFIrAEFoVCoVAoFIElsBwaCoVCoVAoAsuhoVAoFAqFIrAEFoVCoVAoFIElsCgUCoVCoVAElkNDoVAoFArl8oE13S3ydIFFoVAoFApFYJUCax1V698LLAqFQqFQKAKr/SHCvagKlpPAolAoFAqFIrCSA+tmZmZmdulVBNb6a61cwaJQKBQKheIKlocIKRQKhUKhUASWQ0OhUCgUCuWSgeW7CCkUCoVCoQis/CtYfg4WhUKhUCgUgTXwIcLe2xVYFAqFQqFQBJbAolAoFAqFIrAElqNJoVAoFApFYDk0FAqFQqFQBJbAolAoFAqFIrAEFoVCoVAoFIrAcmgoFAqFQqEILIFFoVAoFApFYAksCoVCoVAoAktgOTQUCoVCoVAElsCiUCgUCoUisAQWhUKhUCgUgSWwHBoKhUKhUCgCy6GhUCgUCoUisAQWhUKhUCgUgSWwKBQKhUKhUASWQ0OhUCgUCkVgCSwKhUKhUCgCS2BRKBQKhUKhCCyHhkKhUCgUisASWBQKhUKhUASWwKJQKBQKhSKwBJZDQ6FQKBQKRWAJLAqFQqFQKAJLYFEoFAqFQhFYAsuhoVAoFAqFIrAcGgqFQqFQKAJLYFEoFAqFQhFYAotCoVAoFApFYDk0FAqFQqFQBJbAolAoFAqFIrAEFoVCoVAoFIElsBwaCoVCoVAoAktgUSgUCoVCEVgCi0KhUCgUisASWA4NhUKhUCgUgSWwKBQKhUKhCCyBRaFQKBQKRWAJLIeGQqFQKBSKwHJoKBQKhUKhCCyBRaFQKBQKRWAJLAqFQqFQKBSB5dBQKBQKhUK5fGBNd4s8XWBRKBQKhUIRWKXAuk+iRUt9/b3AolAoFAqFIrDaHyLci6pgOQksCoVCoVAoAis5sG5mZmZml151YG0+PugKFoVCoVAoFFewGq9glYtKYFEoFAqFQhFYdYG1DiOBRaFQKBQKRWC1B9ZeFfkuQgqFQqFQKAKrJbCm1Tb/SGBRKBQKhUIRWHUPEabdrsCiUCgUCoUisAQWhUKhUCgUgSWwHE0KhUKhUCgCy6GhUCgUCoUisAQWhUKhUCgUgSWwKBQKhUKhUASWQ0OhUCgUCkVgCSwKhUKhUCgCS2BRKBQKhUIRWALLoaFQKBQKhSKwBBaFQqFQKBSBJbAoFAqFQqEILIHl0FAoFAqFQhFYDg2FQqFQKBSBJbAoFAqFQqEILIFFoVAoFAqFIrAcGgqFQqFQKAJLYFEoFAqFQhFYAotCoVAoFApFYDk0FAqFQqFQBJbAolAoFAqFIrAEFoVCoVAoFIElsBwaCoVCoVAoAktgUSgUCoVCEVgCi0KhUCgUisASWA4NhUKhUCgUgeXQUCgUCoVCEVgCi0KhUCgUisASWBQKhUKhUCgCy6GhUCgUCoUisAQWhUKhUCgUgSWwKBQKhUKhCCyB5dBQKBQKhUIRWAKLQqFQKBSKwBJYFAqFQqFQBJbAcmgoFAqFQqEILIFFoVAoFApFYAksCoVCoVAoAktgOTQUCoVCoVAElkNDoVAoFApFYAksCoVCoVAoAktgUSgUCoVCoQgsh4ZCoVAoFMq1A2v6ss1aKvypwKJQKBQKhSKwSlew9gKrNpsEFoVCoVAoFIG1G0aLpwTLSWBRKBQKhUIRWMmBdTMzMzO79FzBolAoFAqF4gqWhwgdGgqFQqFQKAJLYFEoFAqFQhFY0cCafRchhUKhUCgUgdUWWNPbLWrJz8GiUCgUCoUisBqvYKXdrsCiUCgUCoUisAQWhUKhUCgUgSWwHE0KhUKhUCgCy6GhUCgUCoUisAQWhUKhUCgUgSWwKBQKhUKhUASWQ0OhUCgUCkVgCSwKhUKhUCgCS2BRKBQKhUIRWALLoaFQKBQKhSKwBBaFQqFQKBSBJbAoFAqFQqEILIHl0FAoFAqFQhFYDg2FQqFQKBSBJbAoFAqFQqEILIFFoVAoFAqFIrAcGgqFQqFQKAJLYFEoFAqFQhFYAotCoVAoFApFYDk0FAqFQqFQBJbAolAoFAqFIrAEFoVCoVAoFIElsBwaCoVCoVAoAktgUSgUCoVCEVgCi0KhUCgUisASWA4NhUKhUCgUgeXQUCgUCoVCEVgCi0KhUCgUisASWBQKhUKhUCgCy6GhUCgUCoUisAQWhUKhUCgUgSWwKBQKhUKhCCyB5dBQKBQKhUIRWAKLQqFQKBSKwBJYFAqFQqFQBJbAcmgoFAqFQqEILIFFoVAoFApFYAksCoVCoVAoAktgOTQUCoVCoVAElkNDoVAoFApFYAksCoVCoVAoAktgUSgUCoVCoQgsh4ZCoVAoFMrlA2u6m8CiUCgUCoUisHICqzmPBBaFQqFQKBSBtQysRRJ1Ntbmi//+66//+vnnvV9/++mn9a+/fvjw52+++cuHD5t/unk7v/3ww9+//fa3H3+kUCgUCoVyeeWPX79//PgSgXXb2p++//7TNPnll19++eWXX37l/vrcGLfT94DA2tznuvz3L79U/fqcvf/47rvP/+tFvIgX8SJexIt4ES+y9+tVrmCZmZmZvewElpmZmdmwwJpTv4vQzMzMTGD9r6uyfg6WmZmZmcAazDR1W0PwNTdi/EWmtxt0J0yrvc97bP1SkVe78Kcplb93I5EbLz9P1o/hvb+Rqr/otjeq+S80eOOD7rG994KqM7Z+tgucsdr3oEHvlbn35LXflub3/drbPOdtSf976fwQ9NKB9fWeanvm4J3b82VkVRHT+bY33MKgN3/xSSvl77Sq7dJfn/L9cHjjh/fhoMDqjLPOe6xwPiM3Xn5bEj8y9rylizjrP2N7NxI5Y+Xn6fxYtHnjPe+Vhdsc+rOp+62q2zzn52w3v+/XRtvQt6X2Q0TPbT71Vy6938Dqf9nav+9xgTXip7ZmBVb6m5b14S/rPerwE2Ht/ZPyt9nzQbbwslmVHL/xwytb6X+PDTc4+h6rOmPl5+n8WFRbe4m3OfqjXNYn8ge+Lf3v+6d9TGj4CJ94xoZ+RhBYp2ZN7ftt2yN3c+vjpM8YWPHHlZ4osHIvFDU8RBi5MtGTC5vX/IO5sHdtf8TfY8P74LMEVsPHovgrlv5e+cDAan5bHhhYPe/7c8fVykGB1fYQYcNtCqzhgTXuS53m7scdGh6Ja36otCr+al//EfEXLIbE16dwDOLvq+Nyoerxo/gH6M57LPhYyeHjWXt3+JmPuUSC5jL3WNt/ojS8VxZCJ+W9dY5dCu1/W8rJPvRt6Xnfnzseuh0RWIe3n/WRP/dtEVhnZ1nnl0adcKGo+bpr7QW5QZcJ1//dGfnoP+KhpcP/uG/7D8TmazBV91i5FDvvsdpLFAUx9x6r/UxZLuPcM7Z5I8EzdviyQwOr9r2yfMkt6721v5OCH2GGnorIfVj7vt9wm6e9Lc91xgRWWl3NNV/l3fN9CkMDqyfFzrm344GV+7KJgVX1sbvn+1mCN3L4rU+1L5seWPHLG1nfzeSMDfrkd85t9vwtj/jbH30qDr9wIuvvZdzHhEueMYGV+fyDuIZvb5x3rqs/PLBGXMCL3z/N/53XfD/0fxfhPPhLtoPfop97jxXOZ9V3ER5eCBx0PeCxZ6zhuwizPpG0XXZNfCgq8Z0ifnKy3pb0U1F7ya3/bRn6MSF4Hg4fpky8zfnZdvbPwXqHPwiq7cLSCT9uqvlrwtpescS/09qfUZTy+kRegf6fUTQisGr/4l7qHoscoeaXTbnH2l6xns+mbe99Ke+Vo89e4Yumq36SWc9tjv5Ml/j3ctrHhGc/Yy9xBcvMzMzsFSawzMzMzASWmZmZmcAyMzMzE1hmZmZmJrDMzMzMBJaZmZmZwDIzMzMzgWVmZmYmsMzMzMwElpnZhT4gFv+Jj/LzFG7zSf+hDzMTWGZW9/m+81/42quNEf9Q4zsJrJ5XT2CZCSwzu35gJX7uv1g6CCwzE1hmlhxY8X/Q/o/fr5//8NYWL1h+DePPvHgdym9F4embSvD5y7ejscwElpm9YmCtG2WzmfZ+E7+1w6tBtc+8rpzyWxF5PQ8Dq+rNFFhmAsvMrh9YhWtLhZaK/Gnz0/ufOf4ig4i218TMBJaZXSSwIk/ffPDrKQKr6iE8gWVmAsvMHhNYhZh451ewOqtIYJmZwDKz3sA652uwRgfW4ZW2+BdObSoNX4OlrswElpm9aGDN9d9FuP6j4HcRjgus4FsR/+6/8tsVvB2BZSawzMxsOz3bytVPcjcTWGZm1h5h7gQzE1hmZgLLzASWmZmZmcAyMzMze839BxjgPj6hQyZuAAAAAElFTkSuQmCC" alt="N content graph" width="800" height="600"/></p></div><div class="module"><h2 id="M7"><img src="data:image/png;base64,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" alt="[WARN]"/>Sequence Length Distribution</h2><p><img class="indented" src="data:image/png;base64,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" alt="Sequence length distribution" width="800" height="600"/></p></div><div class="module"><h2 id="M8"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAEkklEQVR42s2XV2hUaxSF/4nRiaIoiKA+CDYMdsQnS8CAFREVsV4VUR9sWMECVuzYsETsGnvvivVaImhyU+Hq9VUfzKtKkptk5nz3rPkz42RyJskE5Xpgw8yZ8++1Zu+1yzGA+T8t8UPGJP1lTGquMenZxvwh02fd02+/jECOMSNdoEwX6KtrgQJjSv425rtMn3VPv+kZPfvTCLj/MM11WphnTNnnlJRA6fDhsGkTHDsG16/D2bOwfj3OtGmUDhjAZ78/oGd1RmcbTOBPY5JdRxmuo/IvyclBZ/lyeP8ePn6EoiLIyYE3b+D5c3j4EG7fhitXICMDZ8QIiv3+oM7Kh3wlRCDfmFbuwawiY0orOnWCmzfhwwcoLITsbMjKgmfP4MEDuHULLl+2kTh+PESAvXth7Voq+/RBPuRLPutFoOqfZ/1jzL8KK3l5UFAA797B69fw9Cncv29JXboEmZk2HYcOwZ49sG0bbNwIa9aAGzWnd2/kSz69IlGDgEIm1s6UKZCfD2/fwqtX8OQJ3LsHN27AxYtw5gwcPQoHDsDu3bB1K2zYAKtXw7JlsHAhzJ0LM2fipKaGI5FRK4EqwZVXtGtnc/viBTx+DHfvWsFduACnT8ORI7B/P+zaBVu2hETIqlUWeMECmDMHZsyASZNg3DgYNYrK1q2R71hhViMg5X4xJsjOnfDoEdy5A9euwfnzcOqUTUNurgXevBnWrYOVK2HJEli0yGpDaZk4EcaOhZFuNaanw6BB0KsXxT6fhFnoSUC1q/Jxhg61ir56Fc6dg5Mn4fBhq/jKSggE7GcBL14M8+bZUEsfwSCUl8OJEzBkCAwcCP37h8Dp1g2nZUuEEd0nov995iefLxASVKyiX76Eigoil4jouY4doUcPmyIRC18isW8fdO8OXbpA27bgguP388ltWMKqTsC2168lXbtWV/T27bBihRWdQKMvERI5kY0G16XvSllSkoWIsm+uCSvctkME1MfVShkzxipapSRFz54NzZtbR1J7LIlwSmLBVZrJyTXAZY4lEAjNjjABDRP1c6ZO/aHoCROgSZMfh+OR8AJv3NgTPGzCEmaEgCaahgrTp8PSpaAe0KhRzcMicfCgNwmBKx11gMuEJcyaBAQ8axa0aeN9WGFVbmPDHk6HNOHzJU4gkgKVYN++iYNHC1PirYNEjRREROi2TM/QxwPXd6/qkJDjkPAUYbgMv3kdUt7VjOKVmpcmRELd0sOfZxlGGpGi4BU2db2ysprgioxXdZSW2qEU6yclJU4jimrFwXi5C5OIBvcqUYGrjGNTOHgwTufO8VtxtWFUGwmlw6vJiIQmZCx4ixa2p7glXrUlFdY5jstrKyOP9hqx2Jx36ADz54fGdEV9xnH0QhKso5api2Ramu2q7qISdENfr4UkdiVrEIlWrex4Vim6Y9xxR3JCK1nsUlpeX2BX4dp8Qo1IE9XVQ2W/fokvpZ5ruSvMYLxQaycYPRp27Ij0BWfyZIqbNm34Wh7vxUQ1/L1ZM5z27aFnT0LTUwNs/HicYcMoce9pqfkpLya/zavZb/Ny+qvsPyB3ge/Rlc06AAAAAElFTkSuQmCC" alt="[FAIL]"/>Sequence Duplication Levels</h2><p><img class="indented" src="data:image/png;base64,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" alt="Duplication level graph" width="800" height="600"/></p></div><div class="module"><h2 id="M9"><img src="data:image/png;base64,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" alt="[FAIL]"/>Overrepresented sequences</h2><table><thead><tr><th>Sequence</th><th>Count</th><th>Percentage</th><th>Possible Source</th></tr></thead><tbody><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTT</td><td>2628</td><td>30.17568033069239</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGAT</td><td>1004</td><td>11.528304053278218</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG</td><td>139</td><td>1.59605006315306</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGGT</td><td>110</td><td>1.2630612010563786</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGCT</td><td>76</td><td>0.872660466184407</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTTA</td><td>74</td><td>0.8496957170742909</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAGTTCAAGCGTT</td><td>74</td><td>0.8496957170742909</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGG</td><td>72</td><td>0.826730967964175</td><td>No Hit</td></tr><tr><td>AATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTTA</td><td>54</td><td>0.6200482259731313</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAGTTCAAGCGAT</td><td>38</td><td>0.4363302330922035</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGACGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTT</td><td>36</td><td>0.4133654839820875</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCG</td><td>35</td><td>0.40188310942702954</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGG</td><td>28</td><td>0.3215064875416236</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTTAT</td><td>26</td><td>0.29854173843150766</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGTCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTT</td><td>22</td><td>0.25261224021127565</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTGATTCAAGCGTT</td><td>21</td><td>0.24112986565621772</td><td>No Hit</td></tr><tr><td>AATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGATC</td><td>18</td><td>0.20668274199104375</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAGGCGTT</td><td>16</td><td>0.18371799288092777</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAG</td><td>15</td><td>0.17223561832586978</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTTG</td><td>14</td><td>0.1607532437708118</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGGGCGGCTTAATTCAAGCGTT</td><td>14</td><td>0.1607532437708118</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGGTTAATTCAAGCGTT</td><td>14</td><td>0.1607532437708118</td><td>No Hit</td></tr><tr><td>AATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTTG</td><td>13</td><td>0.14927086921575383</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGC</td><td>13</td><td>0.14927086921575383</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGG</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTGAAGCGTT</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTTAG</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTA</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGGGGCGCGGCTTAATTCAAGCGTT</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGGCGCTTCGCGGCGCGGCTTAATTCAAGCGTT</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCACGCGTT</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCGTAATTCAAGCGTT</td><td>11</td><td>0.12630612010563783</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGACGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGAT</td><td>11</td><td>0.12630612010563783</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGATA</td><td>10</td><td>0.11482374555057985</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGC</td><td>10</td><td>0.11482374555057985</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGGGGCTTAATTCAAGCGTT</td><td>10</td><td>0.11482374555057985</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTGAATTCAAGCGTT</td><td>10</td><td>0.11482374555057985</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCTGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTT</td><td>9</td><td>0.10334137099552188</td><td>No Hit</td></tr><tr><td>AATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGATA</td><td>9</td><td>0.10334137099552188</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGAG</td><td>9</td><td>0.10334137099552188</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCGAGCGTT</td><td>9</td><td>0.10334137099552188</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGGGGCTTAATTCAAGCGAT</td><td>9</td><td>0.10334137099552188</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTGATTCAAGCGAT</td><td>9</td><td>0.10334137099552188</td><td>No Hit</td></tr></tbody></table></div><div class="module"><h2 id="M10"><img src="data:image/png;base64,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" alt="[OK]"/>Adapter Content</h2><p><img class="indented" 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" alt="Adapter graph" width="800" height="600"/></p></div></div><div class="footer">Produced by <a href="http://www.bioinformatics.babraham.ac.uk/projects/fastqc/">FastQC</a>  (version 0.11.8)</div></body></html>
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+</style></head><body><div class="header"><div id="header_title"><img src="data:image/png;base64,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" alt="FastQC"/>FastQC Report</div><div id="header_filename">Thu 24 Feb 2022<br/>test.fastq2_trim.fq</div></div><div class="summary"><h2>Summary</h2><ul><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M0">Basic Statistics</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M1">Per base sequence quality</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M2">Per tile sequence quality</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M3">Per sequence quality scores</a></li><li><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAEkklEQVR42s2XV2hUaxSF/4nRiaIoiKA+CDYMdsQnS8CAFREVsV4VUR9sWMECVuzYsETsGnvvivVaImhyU+Hq9VUfzKtKkptk5nz3rPkz42RyJskE5Xpgw8yZ8++1Zu+1yzGA+T8t8UPGJP1lTGquMenZxvwh02fd02+/jECOMSNdoEwX6KtrgQJjSv425rtMn3VPv+kZPfvTCLj/MM11WphnTNnnlJRA6fDhsGkTHDsG16/D2bOwfj3OtGmUDhjAZ78/oGd1RmcbTOBPY5JdRxmuo/IvyclBZ/lyeP8ePn6EoiLIyYE3b+D5c3j4EG7fhitXICMDZ8QIiv3+oM7Kh3wlRCDfmFbuwawiY0orOnWCmzfhwwcoLITsbMjKgmfP4MEDuHULLl+2kTh+PESAvXth7Voq+/RBPuRLPutFoOqfZ/1jzL8KK3l5UFAA797B69fw9Cncv29JXboEmZk2HYcOwZ49sG0bbNwIa9aAGzWnd2/kSz69IlGDgEIm1s6UKZCfD2/fwqtX8OQJ3LsHN27AxYtw5gwcPQoHDsDu3bB1K2zYAKtXw7JlsHAhzJ0LM2fipKaGI5FRK4EqwZVXtGtnc/viBTx+DHfvWsFduACnT8ORI7B/P+zaBVu2hETIqlUWeMECmDMHZsyASZNg3DgYNYrK1q2R71hhViMg5X4xJsjOnfDoEdy5A9euwfnzcOqUTUNurgXevBnWrYOVK2HJEli0yGpDaZk4EcaOhZFuNaanw6BB0KsXxT6fhFnoSUC1q/Jxhg61ir56Fc6dg5Mn4fBhq/jKSggE7GcBL14M8+bZUEsfwSCUl8OJEzBkCAwcCP37h8Dp1g2nZUuEEd0nov995iefLxASVKyiX76Eigoil4jouY4doUcPmyIRC18isW8fdO8OXbpA27bgguP388ltWMKqTsC2168lXbtWV/T27bBihRWdQKMvERI5kY0G16XvSllSkoWIsm+uCSvctkME1MfVShkzxipapSRFz54NzZtbR1J7LIlwSmLBVZrJyTXAZY4lEAjNjjABDRP1c6ZO/aHoCROgSZMfh+OR8AJv3NgTPGzCEmaEgCaahgrTp8PSpaAe0KhRzcMicfCgNwmBKx11gMuEJcyaBAQ8axa0aeN9WGFVbmPDHk6HNOHzJU4gkgKVYN++iYNHC1PirYNEjRREROi2TM/QxwPXd6/qkJDjkPAUYbgMv3kdUt7VjOKVmpcmRELd0sOfZxlGGpGi4BU2db2ysprgioxXdZSW2qEU6yclJU4jimrFwXi5C5OIBvcqUYGrjGNTOHgwTufO8VtxtWFUGwmlw6vJiIQmZCx4ixa2p7glXrUlFdY5jstrKyOP9hqx2Jx36ADz54fGdEV9xnH0QhKso5api2Ramu2q7qISdENfr4UkdiVrEIlWrex4Vim6Y9xxR3JCK1nsUlpeX2BX4dp8Qo1IE9XVQ2W/fokvpZ5ruSvMYLxQaycYPRp27Ij0BWfyZIqbNm34Wh7vxUQ1/L1ZM5z27aFnT0LTUwNs/HicYcMoce9pqfkpLya/zavZb/Ny+qvsPyB3ge/Rlc06AAAAAElFTkSuQmCC" alt="[FAIL]"/><a href="#M4">Per base sequence content</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M5">Per sequence GC content</a></li><li><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAFlUlEQVR42s2XCUzTVxzHybIs0IgCLYqyQ9RtmhjCNKKbikajYVc22NThNjYjeC0yWBESxAV1Ckw8QEUF5ChnS4FyFETucwWU+7ClHKKiImLI4nCz9bv3/pS7ra1HtM1Lm/b/fp/ve+93PQMABq9y6D/Bz+ANNvethWxPw3Xs3wx/YAb9Tn6j/700AeZc1qccrhGPw2UNkk8Fx9voIceX9Tcz6Hf62/B/PPrsCxNgzjW043iyGjheRkOWQRzFt2IH/Nl4DDFyHjJ6siDoSoZ/YwB2VuyEffpGzA5iK+izdA6d+8wCyHa+SYyEsj2N/jU/aaL0vbIf0sF2tA92oOVBG+ruN6CqrwZldypR0FuMnBuXkX49C5GyaGwq3ASLU2ZKOpfaoLb0EmDibmLC8TQq5/iw/vlIaA1xjxiyQTmaH7Sitr8ekr5qlN6pQP6tImTfyIXoeiYEnSmIlSfiooyHc20R8G84htUZq0FtUFvUpk4ChldO4H6sRzvKXdEw0ISmgRZc7a/DXwRccrscebcKIb5xCWndGeB3CsGTJyBCGoPQtnCcajlLjugk/qgPxO+1h7Eqyw7UFrWpbiemCKBbRlW7lrmgcaAZV/prUXm3CsW3y3D5VgGyenKQ2p2OpM5k8NoTEC6Nxtm2MJxsPoPAxhM4XB+AA1cPwbvmADyqvPFLpQdsM1aodoIVqlUAdRp6bgv5HzBbXHFXgqLbpci9mY/MnmykdIuQ2CFATHs8wqRRONN6ASeaTyOg8TgO1fnDl4C9anzhLvHCnkp3uJTvgXOJC7YUOWN+0nww/jTJMSevvsHs+DRlSOsZFPaW4NLNPOLpYgi70pBAwFHtcbhwLRKnW8/jeHMIOecgHKw7iv1XD2Jf9X78KtmHyNZoiOQi/FiyHZsJ+Ov87/DZZUesEq8H+4SxkjLUCmDinISPY74jcm4Oe3RyVyriO/iIksUS8EWEtJ5DUFMwjhIH86s7Ap8rfvCs9oGbxBO7KtwQ3hKBrgdd6H94D3ypgIAdsD7nc6wWb8DyzDWYy58HyhifJ8ZWT5NMoLGCJ48jsZ2COHkSCSkezl+LQHBLKI40BGJLsRPW5qzDskxbLE5bDBuRDWwzV5DV2SGwNhCdAx0Yed172AdeWyyWpa/ColQbzE1+H7MTLcEOmKagrAkCaAqlWWwZf6kqlMY8+gDZ3jXZazEz0Rym8TPUDg+yetl9Kca/HikeIUUmgEXizAnPml2YDsoaSduMAJrHaSrdWvw9AYcR8LBHu0m4eJtvqRGsDS4k8DlJFlPnxM0AZVHmmABSTGg+31GxW+XRAfi51AWztKxaI/zxELNytXDVoCzKHBNAKhotKrsr9zIe7Vq+G5wEs9EJi1I+hFDKx7zkuTrAk7XCGQGERZlTBLiSuN1Ltn2BcMEEeGF3PoaI8dzObFgJ3nsuuHoBqiNwLNgMu+x1ow9SByrsyoNC+ZiBPFb8h5LrhWrhqTKhTnD1R6BywuWZn0zYejq2FTuj/k7tKEz5RPlccLVOOBKG7DATtZO+yXNATW81npD3ZHhaux5wTWE4kohoktA0cWPOelT3SkZFDMNT9ICbwCJplvpEND4Vm8ZqNrJBJWJIT7h5Ioek5a+wRLRUcyoeX4y0GaMiaEjqCn9X8A62le0ADXGLYLbmYjS+HJtGTdf5TLUNa5E1Kc8+8K09iPkJVk8vx+MbEm1H8bTBTjDFF3lfMlmVNipLREt0a0gmt2TPIsKKZEv3Ki5TU2gZt8+1168lm9yU6noc1MO3FDkxYNojhpH+YW2Gnf5Nqbq2nHHMWPVbbZNuA6firQghpZt2TRHSSGwn/eScYPNnb8s1XUxoDFtGWpD6sAgrxSvhSi4juypJ31f6ExwLSNsl/BicAOMXczF5ba5mr83l9GWN/wE1f784zfWjGwAAAABJRU5ErkJg" alt="[PASS]"/><a href="#M6">Per base N content</a></li><li><img src="data:image/png;base64,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" alt="[WARNING]"/><a href="#M7">Sequence Length Distribution</a></li><li><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAEkklEQVR42s2XV2hUaxSF/4nRiaIoiKA+CDYMdsQnS8CAFREVsV4VUR9sWMECVuzYsETsGnvvivVaImhyU+Hq9VUfzKtKkptk5nz3rPkz42RyJskE5Xpgw8yZ8++1Zu+1yzGA+T8t8UPGJP1lTGquMenZxvwh02fd02+/jECOMSNdoEwX6KtrgQJjSv425rtMn3VPv+kZPfvTCLj/MM11WphnTNnnlJRA6fDhsGkTHDsG16/D2bOwfj3OtGmUDhjAZ78/oGd1RmcbTOBPY5JdRxmuo/IvyclBZ/lyeP8ePn6EoiLIyYE3b+D5c3j4EG7fhitXICMDZ8QIiv3+oM7Kh3wlRCDfmFbuwawiY0orOnWCmzfhwwcoLITsbMjKgmfP4MEDuHULLl+2kTh+PESAvXth7Voq+/RBPuRLPutFoOqfZ/1jzL8KK3l5UFAA797B69fw9Cncv29JXboEmZk2HYcOwZ49sG0bbNwIa9aAGzWnd2/kSz69IlGDgEIm1s6UKZCfD2/fwqtX8OQJ3LsHN27AxYtw5gwcPQoHDsDu3bB1K2zYAKtXw7JlsHAhzJ0LM2fipKaGI5FRK4EqwZVXtGtnc/viBTx+DHfvWsFduACnT8ORI7B/P+zaBVu2hETIqlUWeMECmDMHZsyASZNg3DgYNYrK1q2R71hhViMg5X4xJsjOnfDoEdy5A9euwfnzcOqUTUNurgXevBnWrYOVK2HJEli0yGpDaZk4EcaOhZFuNaanw6BB0KsXxT6fhFnoSUC1q/Jxhg61ir56Fc6dg5Mn4fBhq/jKSggE7GcBL14M8+bZUEsfwSCUl8OJEzBkCAwcCP37h8Dp1g2nZUuEEd0nov995iefLxASVKyiX76Eigoil4jouY4doUcPmyIRC18isW8fdO8OXbpA27bgguP388ltWMKqTsC2168lXbtWV/T27bBihRWdQKMvERI5kY0G16XvSllSkoWIsm+uCSvctkME1MfVShkzxipapSRFz54NzZtbR1J7LIlwSmLBVZrJyTXAZY4lEAjNjjABDRP1c6ZO/aHoCROgSZMfh+OR8AJv3NgTPGzCEmaEgCaahgrTp8PSpaAe0KhRzcMicfCgNwmBKx11gMuEJcyaBAQ8axa0aeN9WGFVbmPDHk6HNOHzJU4gkgKVYN++iYNHC1PirYNEjRREROi2TM/QxwPXd6/qkJDjkPAUYbgMv3kdUt7VjOKVmpcmRELd0sOfZxlGGpGi4BU2db2ysprgioxXdZSW2qEU6yclJU4jimrFwXi5C5OIBvcqUYGrjGNTOHgwTufO8VtxtWFUGwmlw6vJiIQmZCx4ixa2p7glXrUlFdY5jstrKyOP9hqx2Jx36ADz54fGdEV9xnH0QhKso5api2Ramu2q7qISdENfr4UkdiVrEIlWrex4Vim6Y9xxR3JCK1nsUlpeX2BX4dp8Qo1IE9XVQ2W/fokvpZ5ruSvMYLxQaycYPRp27Ij0BWfyZIqbNm34Wh7vxUQ1/L1ZM5z27aFnT0LTUwNs/HicYcMoce9pqfkpLya/zavZb/Ny+qvsPyB3ge/Rlc06AAAAAElFTkSuQmCC" alt="[FAIL]"/><a href="#M8">Sequence Duplication Levels</a></li><li><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAEkklEQVR42s2XV2hUaxSF/4nRiaIoiKA+CDYMdsQnS8CAFREVsV4VUR9sWMECVuzYsETsGnvvivVaImhyU+Hq9VUfzKtKkptk5nz3rPkz42RyJskE5Xpgw8yZ8++1Zu+1yzGA+T8t8UPGJP1lTGquMenZxvwh02fd02+/jECOMSNdoEwX6KtrgQJjSv425rtMn3VPv+kZPfvTCLj/MM11WphnTNnnlJRA6fDhsGkTHDsG16/D2bOwfj3OtGmUDhjAZ78/oGd1RmcbTOBPY5JdRxmuo/IvyclBZ/lyeP8ePn6EoiLIyYE3b+D5c3j4EG7fhitXICMDZ8QIiv3+oM7Kh3wlRCDfmFbuwawiY0orOnWCmzfhwwcoLITsbMjKgmfP4MEDuHULLl+2kTh+PESAvXth7Voq+/RBPuRLPutFoOqfZ/1jzL8KK3l5UFAA797B69fw9Cncv29JXboEmZk2HYcOwZ49sG0bbNwIa9aAGzWnd2/kSz69IlGDgEIm1s6UKZCfD2/fwqtX8OQJ3LsHN27AxYtw5gwcPQoHDsDu3bB1K2zYAKtXw7JlsHAhzJ0LM2fipKaGI5FRK4EqwZVXtGtnc/viBTx+DHfvWsFduACnT8ORI7B/P+zaBVu2hETIqlUWeMECmDMHZsyASZNg3DgYNYrK1q2R71hhViMg5X4xJsjOnfDoEdy5A9euwfnzcOqUTUNurgXevBnWrYOVK2HJEli0yGpDaZk4EcaOhZFuNaanw6BB0KsXxT6fhFnoSUC1q/Jxhg61ir56Fc6dg5Mn4fBhq/jKSggE7GcBL14M8+bZUEsfwSCUl8OJEzBkCAwcCP37h8Dp1g2nZUuEEd0nov995iefLxASVKyiX76Eigoil4jouY4doUcPmyIRC18isW8fdO8OXbpA27bgguP388ltWMKqTsC2168lXbtWV/T27bBihRWdQKMvERI5kY0G16XvSllSkoWIsm+uCSvctkME1MfVShkzxipapSRFz54NzZtbR1J7LIlwSmLBVZrJyTXAZY4lEAjNjjABDRP1c6ZO/aHoCROgSZMfh+OR8AJv3NgTPGzCEmaEgCaahgrTp8PSpaAe0KhRzcMicfCgNwmBKx11gMuEJcyaBAQ8axa0aeN9WGFVbmPDHk6HNOHzJU4gkgKVYN++iYNHC1PirYNEjRREROi2TM/QxwPXd6/qkJDjkPAUYbgMv3kdUt7VjOKVmpcmRELd0sOfZxlGGpGi4BU2db2ysprgioxXdZSW2qEU6yclJU4jimrFwXi5C5OIBvcqUYGrjGNTOHgwTufO8VtxtWFUGwmlw6vJiIQmZCx4ixa2p7glXrUlFdY5jstrKyOP9hqx2Jx36ADz54fGdEV9xnH0QhKso5api2Ramu2q7qISdENfr4UkdiVrEIlWrex4Vim6Y9xxR3JCK1nsUlpeX2BX4dp8Qo1IE9XVQ2W/fokvpZ5ruSvMYLxQaycYPRp27Ij0BWfyZIqbNm34Wh7vxUQ1/L1ZM5z27aFnT0LTUwNs/HicYcMoce9pqfkpLya/zavZb/Ny+qvsPyB3ge/Rlc06AAAAAElFTkSuQmCC" alt="[FAIL]"/><a href="#M9">Overrepresented sequences</a></li><li><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAFlUlEQVR42s2XCUzTVxzHybIs0IgCLYqyQ9RtmhjCNKKbikajYVc22NThNjYjeC0yWBESxAV1Ckw8QEUF5ChnS4FyFETucwWU+7ClHKKiImLI4nCz9bv3/pS7ra1HtM1Lm/b/fp/ve+93PQMABq9y6D/Bz+ANNvethWxPw3Xs3wx/YAb9Tn6j/700AeZc1qccrhGPw2UNkk8Fx9voIceX9Tcz6Hf62/B/PPrsCxNgzjW043iyGjheRkOWQRzFt2IH/Nl4DDFyHjJ6siDoSoZ/YwB2VuyEffpGzA5iK+izdA6d+8wCyHa+SYyEsj2N/jU/aaL0vbIf0sF2tA92oOVBG+ruN6CqrwZldypR0FuMnBuXkX49C5GyaGwq3ASLU2ZKOpfaoLb0EmDibmLC8TQq5/iw/vlIaA1xjxiyQTmaH7Sitr8ekr5qlN6pQP6tImTfyIXoeiYEnSmIlSfiooyHc20R8G84htUZq0FtUFvUpk4ChldO4H6sRzvKXdEw0ISmgRZc7a/DXwRccrscebcKIb5xCWndGeB3CsGTJyBCGoPQtnCcajlLjugk/qgPxO+1h7Eqyw7UFrWpbiemCKBbRlW7lrmgcaAZV/prUXm3CsW3y3D5VgGyenKQ2p2OpM5k8NoTEC6Nxtm2MJxsPoPAxhM4XB+AA1cPwbvmADyqvPFLpQdsM1aodoIVqlUAdRp6bgv5HzBbXHFXgqLbpci9mY/MnmykdIuQ2CFATHs8wqRRONN6ASeaTyOg8TgO1fnDl4C9anzhLvHCnkp3uJTvgXOJC7YUOWN+0nww/jTJMSevvsHs+DRlSOsZFPaW4NLNPOLpYgi70pBAwFHtcbhwLRKnW8/jeHMIOecgHKw7iv1XD2Jf9X78KtmHyNZoiOQi/FiyHZsJ+Ov87/DZZUesEq8H+4SxkjLUCmDinISPY74jcm4Oe3RyVyriO/iIksUS8EWEtJ5DUFMwjhIH86s7Ap8rfvCs9oGbxBO7KtwQ3hKBrgdd6H94D3ypgIAdsD7nc6wWb8DyzDWYy58HyhifJ8ZWT5NMoLGCJ48jsZ2COHkSCSkezl+LQHBLKI40BGJLsRPW5qzDskxbLE5bDBuRDWwzV5DV2SGwNhCdAx0Yed172AdeWyyWpa/ColQbzE1+H7MTLcEOmKagrAkCaAqlWWwZf6kqlMY8+gDZ3jXZazEz0Rym8TPUDg+yetl9Kca/HikeIUUmgEXizAnPml2YDsoaSduMAJrHaSrdWvw9AYcR8LBHu0m4eJtvqRGsDS4k8DlJFlPnxM0AZVHmmABSTGg+31GxW+XRAfi51AWztKxaI/zxELNytXDVoCzKHBNAKhotKrsr9zIe7Vq+G5wEs9EJi1I+hFDKx7zkuTrAk7XCGQGERZlTBLiSuN1Ltn2BcMEEeGF3PoaI8dzObFgJ3nsuuHoBqiNwLNgMu+x1ow9SByrsyoNC+ZiBPFb8h5LrhWrhqTKhTnD1R6BywuWZn0zYejq2FTuj/k7tKEz5RPlccLVOOBKG7DATtZO+yXNATW81npD3ZHhaux5wTWE4kohoktA0cWPOelT3SkZFDMNT9ICbwCJplvpEND4Vm8ZqNrJBJWJIT7h5Ioek5a+wRLRUcyoeX4y0GaMiaEjqCn9X8A62le0ADXGLYLbmYjS+HJtGTdf5TLUNa5E1Kc8+8K09iPkJVk8vx+MbEm1H8bTBTjDFF3lfMlmVNipLREt0a0gmt2TPIsKKZEv3Ki5TU2gZt8+1168lm9yU6noc1MO3FDkxYNojhpH+YW2Gnf5Nqbq2nHHMWPVbbZNuA6firQghpZt2TRHSSGwn/eScYPNnb8s1XUxoDFtGWpD6sAgrxSvhSi4juypJ31f6ExwLSNsl/BicAOMXczF5ba5mr83l9GWN/wE1f784zfWjGwAAAABJRU5ErkJg" alt="[PASS]"/><a href="#M10">Adapter Content</a></li></ul></div><div class="main"><div class="module"><h2 id="M0"><img src="data:image/png;base64,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" alt="[OK]"/>Basic Statistics</h2><table><thead><tr><th>Measure</th><th>Value</th></tr></thead><tbody><tr><td>Filename</td><td>test.fastq2_trim.fq</td></tr><tr><td>File type</td><td>Conventional base calls</td></tr><tr><td>Encoding</td><td>Sanger / Illumina 1.9</td></tr><tr><td>Total Sequences</td><td>8709</td></tr><tr><td>Sequences flagged as poor quality</td><td>0</td></tr><tr><td>Sequence length</td><td>30-175</td></tr><tr><td>%GC</td><td>54</td></tr></tbody></table></div><div class="module"><h2 id="M1"><img src="data:image/png;base64,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" alt="[OK]"/>Per base sequence quality</h2><p><img class="indented" 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" alt="Per base quality graph" width="800" height="600"/></p></div><div class="module"><h2 id="M2"><img src="data:image/png;base64,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" alt="[OK]"/>Per tile sequence quality</h2><p><img class="indented" src="data:image/png;base64,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" alt="Per base quality graph" width="800" height="600"/></p></div><div class="module"><h2 id="M3"><img src="data:image/png;base64,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" alt="[OK]"/>Per sequence quality scores</h2><p><img class="indented" 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" alt="Per Sequence quality graph" width="800" height="600"/></p></div><div class="module"><h2 id="M4"><img src="data:image/png;base64,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" alt="[FAIL]"/>Per base sequence content</h2><p><img class="indented" src="data:image/png;base64,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" alt="Per base sequence content" width="800" height="600"/></p></div><div class="module"><h2 id="M5"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAFlUlEQVR42s2XCUzTVxzHybIs0IgCLYqyQ9RtmhjCNKKbikajYVc22NThNjYjeC0yWBESxAV1Ckw8QEUF5ChnS4FyFETucwWU+7ClHKKiImLI4nCz9bv3/pS7ra1HtM1Lm/b/fp/ve+93PQMABq9y6D/Bz+ANNvethWxPw3Xs3wx/YAb9Tn6j/700AeZc1qccrhGPw2UNkk8Fx9voIceX9Tcz6Hf62/B/PPrsCxNgzjW043iyGjheRkOWQRzFt2IH/Nl4DDFyHjJ6siDoSoZ/YwB2VuyEffpGzA5iK+izdA6d+8wCyHa+SYyEsj2N/jU/aaL0vbIf0sF2tA92oOVBG+ruN6CqrwZldypR0FuMnBuXkX49C5GyaGwq3ASLU2ZKOpfaoLb0EmDibmLC8TQq5/iw/vlIaA1xjxiyQTmaH7Sitr8ekr5qlN6pQP6tImTfyIXoeiYEnSmIlSfiooyHc20R8G84htUZq0FtUFvUpk4ChldO4H6sRzvKXdEw0ISmgRZc7a/DXwRccrscebcKIb5xCWndGeB3CsGTJyBCGoPQtnCcajlLjugk/qgPxO+1h7Eqyw7UFrWpbiemCKBbRlW7lrmgcaAZV/prUXm3CsW3y3D5VgGyenKQ2p2OpM5k8NoTEC6Nxtm2MJxsPoPAxhM4XB+AA1cPwbvmADyqvPFLpQdsM1aodoIVqlUAdRp6bgv5HzBbXHFXgqLbpci9mY/MnmykdIuQ2CFATHs8wqRRONN6ASeaTyOg8TgO1fnDl4C9anzhLvHCnkp3uJTvgXOJC7YUOWN+0nww/jTJMSevvsHs+DRlSOsZFPaW4NLNPOLpYgi70pBAwFHtcbhwLRKnW8/jeHMIOecgHKw7iv1XD2Jf9X78KtmHyNZoiOQi/FiyHZsJ+Ov87/DZZUesEq8H+4SxkjLUCmDinISPY74jcm4Oe3RyVyriO/iIksUS8EWEtJ5DUFMwjhIH86s7Ap8rfvCs9oGbxBO7KtwQ3hKBrgdd6H94D3ypgIAdsD7nc6wWb8DyzDWYy58HyhifJ8ZWT5NMoLGCJ48jsZ2COHkSCSkezl+LQHBLKI40BGJLsRPW5qzDskxbLE5bDBuRDWwzV5DV2SGwNhCdAx0Yed172AdeWyyWpa/ColQbzE1+H7MTLcEOmKagrAkCaAqlWWwZf6kqlMY8+gDZ3jXZazEz0Rym8TPUDg+yetl9Kca/HikeIUUmgEXizAnPml2YDsoaSduMAJrHaSrdWvw9AYcR8LBHu0m4eJtvqRGsDS4k8DlJFlPnxM0AZVHmmABSTGg+31GxW+XRAfi51AWztKxaI/zxELNytXDVoCzKHBNAKhotKrsr9zIe7Vq+G5wEs9EJi1I+hFDKx7zkuTrAk7XCGQGERZlTBLiSuN1Ltn2BcMEEeGF3PoaI8dzObFgJ3nsuuHoBqiNwLNgMu+x1ow9SByrsyoNC+ZiBPFb8h5LrhWrhqTKhTnD1R6BywuWZn0zYejq2FTuj/k7tKEz5RPlccLVOOBKG7DATtZO+yXNATW81npD3ZHhaux5wTWE4kohoktA0cWPOelT3SkZFDMNT9ICbwCJplvpEND4Vm8ZqNrJBJWJIT7h5Ioek5a+wRLRUcyoeX4y0GaMiaEjqCn9X8A62le0ADXGLYLbmYjS+HJtGTdf5TLUNa5E1Kc8+8K09iPkJVk8vx+MbEm1H8bTBTjDFF3lfMlmVNipLREt0a0gmt2TPIsKKZEv3Ki5TU2gZt8+1168lm9yU6noc1MO3FDkxYNojhpH+YW2Gnf5Nqbq2nHHMWPVbbZNuA6firQghpZt2TRHSSGwn/eScYPNnb8s1XUxoDFtGWpD6sAgrxSvhSi4juypJ31f6ExwLSNsl/BicAOMXczF5ba5mr83l9GWN/wE1f784zfWjGwAAAABJRU5ErkJg" alt="[OK]"/>Per sequence GC content</h2><p><img class="indented" src="data:image/png;base64,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" alt="Per sequence GC content graph" width="800" height="600"/></p></div><div class="module"><h2 id="M6"><img src="data:image/png;base64,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" alt="[OK]"/>Per base N content</h2><p><img class="indented" 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" alt="N content graph" width="800" height="600"/></p></div><div class="module"><h2 id="M7"><img src="data:image/png;base64,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" alt="[WARN]"/>Sequence Length Distribution</h2><p><img class="indented" src="data:image/png;base64,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" alt="Sequence length distribution" width="800" height="600"/></p></div><div class="module"><h2 id="M8"><img src="data:image/png;base64,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" alt="[FAIL]"/>Sequence Duplication Levels</h2><p><img class="indented" src="data:image/png;base64,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" alt="Duplication level graph" width="800" height="600"/></p></div><div class="module"><h2 id="M9"><img src="data:image/png;base64,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" alt="[FAIL]"/>Overrepresented sequences</h2><table><thead><tr><th>Sequence</th><th>Count</th><th>Percentage</th><th>Possible Source</th></tr></thead><tbody><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTT</td><td>2628</td><td>30.17568033069239</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGAT</td><td>1004</td><td>11.528304053278218</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG</td><td>139</td><td>1.59605006315306</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGGT</td><td>110</td><td>1.2630612010563786</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGCT</td><td>76</td><td>0.872660466184407</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTTA</td><td>74</td><td>0.8496957170742909</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAGTTCAAGCGTT</td><td>74</td><td>0.8496957170742909</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGG</td><td>72</td><td>0.826730967964175</td><td>No Hit</td></tr><tr><td>AATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTTA</td><td>54</td><td>0.6200482259731313</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAGTTCAAGCGAT</td><td>38</td><td>0.4363302330922035</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGACGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTT</td><td>36</td><td>0.4133654839820875</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCG</td><td>35</td><td>0.40188310942702954</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGG</td><td>28</td><td>0.3215064875416236</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTTAT</td><td>26</td><td>0.29854173843150766</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGTCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTT</td><td>22</td><td>0.25261224021127565</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTGATTCAAGCGTT</td><td>21</td><td>0.24112986565621772</td><td>No Hit</td></tr><tr><td>AATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGATC</td><td>18</td><td>0.20668274199104375</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAGGCGTT</td><td>16</td><td>0.18371799288092777</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAG</td><td>15</td><td>0.17223561832586978</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTTG</td><td>14</td><td>0.1607532437708118</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGGGCGGCTTAATTCAAGCGTT</td><td>14</td><td>0.1607532437708118</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGGTTAATTCAAGCGTT</td><td>14</td><td>0.1607532437708118</td><td>No Hit</td></tr><tr><td>AATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTTG</td><td>13</td><td>0.14927086921575383</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGC</td><td>13</td><td>0.14927086921575383</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGG</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTGAAGCGTT</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTTAG</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTA</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGGGGCGCGGCTTAATTCAAGCGTT</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGGCGCTTCGCGGCGCGGCTTAATTCAAGCGTT</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCACGCGTT</td><td>12</td><td>0.13778849466069584</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCGTAATTCAAGCGTT</td><td>11</td><td>0.12630612010563783</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGACGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGAT</td><td>11</td><td>0.12630612010563783</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGATA</td><td>10</td><td>0.11482374555057985</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGC</td><td>10</td><td>0.11482374555057985</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGGGGCTTAATTCAAGCGTT</td><td>10</td><td>0.11482374555057985</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTGAATTCAAGCGTT</td><td>10</td><td>0.11482374555057985</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCTGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGTT</td><td>9</td><td>0.10334137099552188</td><td>No Hit</td></tr><tr><td>AATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGATA</td><td>9</td><td>0.10334137099552188</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCGAG</td><td>9</td><td>0.10334137099552188</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCGAGCGTT</td><td>9</td><td>0.10334137099552188</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGGGGCTTAATTCAAGCGAT</td><td>9</td><td>0.10334137099552188</td><td>No Hit</td></tr><tr><td>CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTGATTCAAGCGAT</td><td>9</td><td>0.10334137099552188</td><td>No Hit</td></tr></tbody></table></div><div class="module"><h2 id="M10"><img src="data:image/png;base64,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" alt="[OK]"/>Adapter Content</h2><p><img class="indented" 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" alt="Adapter graph" width="800" height="600"/></p></div></div><div class="footer">Produced by <a href="http://www.bioinformatics.babraham.ac.uk/projects/fastqc/">FastQC</a>  (version 0.11.8)</div></body></html>
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-</style></head><body><div class="header"><div id="header_title"><img src="data:image/png;base64,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" alt="FastQC"/>FastQC Report</div><div id="header_filename">Tue 22 Feb 2022<br/>test.fastq2_5pAtccRm.fq</div></div><div class="summary"><h2>Summary</h2><ul><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M0">Basic Statistics</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M1">Per base sequence quality</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M2">Per tile sequence quality</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M3">Per sequence quality scores</a></li><li><img src="data:image/png;base64,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" alt="[FAIL]"/><a href="#M4">Per base sequence content</a></li><li><img src="data:image/png;base64,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" alt="[FAIL]"/><a href="#M5">Per sequence GC content</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M6">Per base N content</a></li><li><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAEpklEQVR42s1XfUyUdRz/URrktNpaW/aHW1LLNdN0+U9WSzdfcq31/uLrWvZP+Y/2T+mc54GplSCOt4CBgqicpICGwokvSYkc3B3nQJxmBSo0K6fsiJe759Pn+zzccRx3xyGwvO07fvye5/f9fH7f90cBUP+nDP+QSd1XZ1LT6hPU/FqzWi4ia9mTZ2NGwLZZvUag/Dqzul2XoDzOROVu3KI6RGQte/JM3pF3R41AbaJ6pT5RNdgT1L+tyXGezpJFgM0MNGYDV34ALhUAtZugWZeh0/IiWpNiPfKunJGzd03glEmNo6L0erPqbkse59WqvwD+bgJuXQL+cgF/2oAbPwPXTgJ/HAOulgKXLYArHdqRxWjfGeuVs6JDdA2LgMOkHrGbVbVri+rsyZ9K5YeBfy4CNxsIXEvgaqC1Cvi9nM9KCFwENNMSjTk6ATiSgfMb0XtgJkSH6BKdURHQb84DzVtVl5gVN+0UJ9B+Hrh+lsAnjBsL+K8Ev3KQbtgLXMgkcBJQt5Xgm4Fz6wFaTds/A6JLdIayxCACYjJhrVV+RGAHgWsI/BPQYgV+O0rQQ1xXAJ4uwNvNv5TeTuBiHoFNwC9fAWfXAWfWACc/BayroBVOMyxB3REJ6AFHv/XkTuZN6dvrpwlWSeAjfQG3j0C7DRKaB/6frF2pBF4LnP4cqFpN4JXA8Q+AH98CypagN+dRiO7gwBxAQCK3bYfywv4NzcxbXi0jcDGBC4GmPMPMDSmGv4MJ1G8n8CdA5XLg2PsEfpPAzMbD84Hil4B9z6E9KcYrGCEJSO5K+mhlC/oimr5tpm+bcgmcATh3EoTEbAnG/4EEvL1AzUYCvwccfQMoXUzgeQSeCxS9oIOj4BloWQ9DMALrRP/tWUBavovx6PkdGNHOZON25zZQ+RLAMpumfYegPQEEuLby5haCWeYYoPtnAoXPAvlPAbmPAwRHZixavlUewRpIQMorq5h7z9NGgXGl9UX0Nj2SYZnFw+OBdGVI8Rwj+Hw/Wcue73kEuZOiIFi+sq0TkDoupRTlNJ9jR18qmQyfZk8crGgEBDSKXrald/gISDOReo7KpQTexFT6kv58l7d+ILSiERAQESzB9BOQjiZNBdYVRipVsAZk3B9eyQgJCJZgDiYgwFUfM2gei6xktAn4XVDCFCx6fmglo+0CfxCyZEY0/VgFoS8N7+yKie4WAtZ1iz3AbYisR5KG/kLEIhEVgawJLDLxA0X2hjqXGRemEAWUYm9adH7Ui9PlA4bIOtK7GezCRS9D2xMfvhQPaEbRWKCjpT8GZB3OAlmT2JRYU8pXGFNSuGYU2I67U4cgUPrq4G4oe8Hv7Z4CnPiMLXoderKjaMeBA0lEV+Q8BLjb+gnIWvb8Jmd8FROnmlW15mt4C+KjG0iCR7KIJKRty8AiIms/OY5+Vk5CNvYURwY0tuRhjWTBQ+mQ7vDJ93H65AMbu2gDO6p9F4fS2cMfSkOO5QzMkNYQU+c/SeDX+W3AmeECpyZnKrTjH6I95cG7H8vDfZhIDnekTYCW9wSnnOnsmOyeFWxg5W9DK10I997pzPOY0fkwuWc+ze6Zj9Oxkv8AsrpUzUM9ceYAAAAASUVORK5C" alt="[WARNING]"/><a href="#M7">Sequence Length Distribution</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M8">Sequence Duplication Levels</a></li><li><img src="data:image/png;base64,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" alt="[FAIL]"/><a href="#M9">Overrepresented sequences</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M10">Adapter Content</a></li></ul></div><div class="main"><div class="module"><h2 id="M0"><img src="data:image/png;base64,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" alt="[OK]"/>Basic Statistics</h2><table><thead><tr><th>Measure</th><th>Value</th></tr></thead><tbody><tr><td>Filename</td><td>test.fastq2_5pAtccRm.fq</td></tr><tr><td>File type</td><td>Conventional base calls</td></tr><tr><td>Encoding</td><td>Sanger / Illumina 1.9</td></tr><tr><td>Total Sequences</td><td>4391</td></tr><tr><td>Sequences flagged as poor quality</td><td>0</td></tr><tr><td>Sequence length</td><td>1-127</td></tr><tr><td>%GC</td><td>52</td></tr></tbody></table></div><div class="module"><h2 id="M1"><img src="data:image/png;base64,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" alt="[OK]"/>Per base sequence quality</h2><p><img class="indented" 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" alt="Per base quality graph" width="1020" height="600"/></p></div><div class="module"><h2 id="M2"><img src="data:image/png;base64,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" alt="[OK]"/>Per tile sequence quality</h2><p><img class="indented" src="data:image/png;base64,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" alt="Per base quality graph" width="1020" height="600"/></p></div><div class="module"><h2 id="M3"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAFlUlEQVR42s2XCUzTVxzHybIs0IgCLYqyQ9RtmhjCNKKbikajYVc22NThNjYjeC0yWBESxAV1Ckw8QEUF5ChnS4FyFETucwWU+7ClHKKiImLI4nCz9bv3/pS7ra1HtM1Lm/b/fp/ve+93PQMABq9y6D/Bz+ANNvethWxPw3Xs3wx/YAb9Tn6j/700AeZc1qccrhGPw2UNkk8Fx9voIceX9Tcz6Hf62/B/PPrsCxNgzjW043iyGjheRkOWQRzFt2IH/Nl4DDFyHjJ6siDoSoZ/YwB2VuyEffpGzA5iK+izdA6d+8wCyHa+SYyEsj2N/jU/aaL0vbIf0sF2tA92oOVBG+ruN6CqrwZldypR0FuMnBuXkX49C5GyaGwq3ASLU2ZKOpfaoLb0EmDibmLC8TQq5/iw/vlIaA1xjxiyQTmaH7Sitr8ekr5qlN6pQP6tImTfyIXoeiYEnSmIlSfiooyHc20R8G84htUZq0FtUFvUpk4ChldO4H6sRzvKXdEw0ISmgRZc7a/DXwRccrscebcKIb5xCWndGeB3CsGTJyBCGoPQtnCcajlLjugk/qgPxO+1h7Eqyw7UFrWpbiemCKBbRlW7lrmgcaAZV/prUXm3CsW3y3D5VgGyenKQ2p2OpM5k8NoTEC6Nxtm2MJxsPoPAxhM4XB+AA1cPwbvmADyqvPFLpQdsM1aodoIVqlUAdRp6bgv5HzBbXHFXgqLbpci9mY/MnmykdIuQ2CFATHs8wqRRONN6ASeaTyOg8TgO1fnDl4C9anzhLvHCnkp3uJTvgXOJC7YUOWN+0nww/jTJMSevvsHs+DRlSOsZFPaW4NLNPOLpYgi70pBAwFHtcbhwLRKnW8/jeHMIOecgHKw7iv1XD2Jf9X78KtmHyNZoiOQi/FiyHZsJ+Ov87/DZZUesEq8H+4SxkjLUCmDinISPY74jcm4Oe3RyVyriO/iIksUS8EWEtJ5DUFMwjhIH86s7Ap8rfvCs9oGbxBO7KtwQ3hKBrgdd6H94D3ypgIAdsD7nc6wWb8DyzDWYy58HyhifJ8ZWT5NMoLGCJ48jsZ2COHkSCSkezl+LQHBLKI40BGJLsRPW5qzDskxbLE5bDBuRDWwzV5DV2SGwNhCdAx0Yed172AdeWyyWpa/ColQbzE1+H7MTLcEOmKagrAkCaAqlWWwZf6kqlMY8+gDZ3jXZazEz0Rym8TPUDg+yetl9Kca/HikeIUUmgEXizAnPml2YDsoaSduMAJrHaSrdWvw9AYcR8LBHu0m4eJtvqRGsDS4k8DlJFlPnxM0AZVHmmABSTGg+31GxW+XRAfi51AWztKxaI/zxELNytXDVoCzKHBNAKhotKrsr9zIe7Vq+G5wEs9EJi1I+hFDKx7zkuTrAk7XCGQGERZlTBLiSuN1Ltn2BcMEEeGF3PoaI8dzObFgJ3nsuuHoBqiNwLNgMu+x1ow9SByrsyoNC+ZiBPFb8h5LrhWrhqTKhTnD1R6BywuWZn0zYejq2FTuj/k7tKEz5RPlccLVOOBKG7DATtZO+yXNATW81npD3ZHhaux5wTWE4kohoktA0cWPOelT3SkZFDMNT9ICbwCJplvpEND4Vm8ZqNrJBJWJIT7h5Ioek5a+wRLRUcyoeX4y0GaMiaEjqCn9X8A62le0ADXGLYLbmYjS+HJtGTdf5TLUNa5E1Kc8+8K09iPkJVk8vx+MbEm1H8bTBTjDFF3lfMlmVNipLREt0a0gmt2TPIsKKZEv3Ki5TU2gZt8+1168lm9yU6noc1MO3FDkxYNojhpH+YW2Gnf5Nqbq2nHHMWPVbbZNuA6firQghpZt2TRHSSGwn/eScYPNnb8s1XUxoDFtGWpD6sAgrxSvhSi4juypJ31f6ExwLSNsl/BicAOMXczF5ba5mr83l9GWN/wE1f784zfWjGwAAAABJRU5ErkJg" alt="[OK]"/>Per sequence quality scores</h2><p><img class="indented" src="data:image/png;base64,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" alt="Per Sequence quality graph" width="800" height="600"/></p></div><div class="module"><h2 id="M4"><img src="data:image/png;base64,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" alt="[FAIL]"/>Per base sequence content</h2><p><img class="indented" 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" alt="Per base sequence content" width="1020" height="600"/></p></div><div class="module"><h2 id="M5"><img src="data:image/png;base64,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" alt="[FAIL]"/>Per sequence GC content</h2><p><img class="indented" src="data:image/png;base64,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" alt="Per sequence GC content graph" width="800" height="600"/></p></div><div class="module"><h2 id="M6"><img src="data:image/png;base64,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" alt="[OK]"/>Per base N content</h2><p><img class="indented" 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" alt="N content graph" width="1020" height="600"/></p></div><div class="module"><h2 id="M7"><img src="data:image/png;base64,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" alt="[WARN]"/>Sequence Length Distribution</h2><p><img class="indented" src="data:image/png;base64,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" alt="Sequence length distribution" width="800" height="600"/></p></div><div class="module"><h2 id="M8"><img src="data:image/png;base64,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" alt="[OK]"/>Sequence Duplication Levels</h2><p><img class="indented" src="data:image/png;base64,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" alt="Duplication level graph" width="800" height="600"/></p></div><div class="module"><h2 id="M9"><img src="data:image/png;base64,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" alt="[FAIL]"/>Overrepresented sequences</h2><table><thead><tr><th>Sequence</th><th>Count</th><th>Percentage</th><th>Possible Source</th></tr></thead><tbody><tr><td>TTAGACGGATCCACTAGTTCTAGAGCGGCCGCCACCGCGGTGGAGCTCCA</td><td>146</td><td>3.3249829196082894</td><td>No Hit</td></tr><tr><td>TT</td><td>92</td><td>2.0951947164654974</td><td>No Hit</td></tr><tr><td>TTATACAGCAAGCGCGCACCGACTCTGACAATCGGCATATCCGGTTCGCC</td><td>86</td><td>1.958551582782965</td><td>No Hit</td></tr><tr><td>TTAAAACCTCTTCAAATTTGCCGTGCAAATTTGGTAGGCCTGAGTGGACT</td><td>83</td><td>1.890230015941699</td><td>No Hit</td></tr><tr><td>TTA</td><td>74</td><td>1.6852653154179003</td><td>No Hit</td></tr><tr><td>TTGGCGAAGTAATCGCAACATCCGCATTAAAATCTAGCGAGGGCTTTACT</td><td>50</td><td>1.1386927806877705</td><td>No Hit</td></tr><tr><td>TTTACCAGCATTAAGGAACAGCTGCTTACGGTCGGCGTGGGTTGCCAGCA</td><td>32</td><td>0.7287633796401731</td><td>No Hit</td></tr><tr><td>ATCACAGGCGTAAACGTCGCCGTTGTGCTCAACAATCACCGAGCGCCCAC</td><td>30</td><td>0.6832156684126622</td><td>No Hit</td></tr><tr><td>TTAT</td><td>26</td><td>0.5921202459576406</td><td>No Hit</td></tr><tr><td>AT</td><td>23</td><td>0.5237986791163743</td><td>No Hit</td></tr><tr><td>GTACGATGTCACTGTGCACGACGATGGTCACTTCCAAGGCGCGGAGTGCC</td><td>19</td><td>0.43270325666135273</td><td>No Hit</td></tr><tr><td>ATCATCGTACGCAAGTGACCAACGCTGTCGATGGTGTCTTTGATGCCAAC</td><td>17</td><td>0.38715554543384195</td><td>No Hit</td></tr><tr><td>TTATCCAGCGCGAGCACTCGCTCTATCACCATTTCACGAGTTTCAAGGTT</td><td>16</td><td>0.36438168982008656</td><td>No Hit</td></tr><tr><td>ATGAGGAGCGAAGGCATGAAACCATATCAGCGCCAGTTTATTGAATTTGC</td><td>16</td><td>0.36438168982008656</td><td>No Hit</td></tr><tr><td>ATATAGAGCATTTTTGCCTCCTTTCGCGCCACAAGAAATTAACTGTAGCG</td><td>15</td><td>0.3416078342063311</td><td>No Hit</td></tr><tr><td>TTAGGCGACAACGTGATGGTTGCGCCGGTGTTCACTGAAGCGGGCGATGT</td><td>14</td><td>0.31883397859257573</td><td>No Hit</td></tr><tr><td>TTG</td><td>14</td><td>0.31883397859257573</td><td>No Hit</td></tr><tr><td>TTATCAATACTGCCTTCAATCAGTACATTGGTGGCAGGAACATCATTGAG</td><td>14</td><td>0.31883397859257573</td><td>No Hit</td></tr><tr><td>TTATCCGAAGCGATGAGAGTTATCCCGTAACCGGGTCAGCCACTGCATAG</td><td>14</td><td>0.31883397859257573</td><td>No Hit</td></tr><tr><td>TTACGCATAGTCATTTCTCCTTCTAAGAAGCGAGTAAGTACCTGCAAATC</td><td>13</td><td>0.2960601229788203</td><td>No Hit</td></tr><tr><td>TTACGCATAATCAATAGCTCCTGAAATCAGCGAGAATGTAAGACCTTCCA</td><td>12</td><td>0.2732862673650649</td><td>No Hit</td></tr><tr><td>TTAG</td><td>12</td><td>0.2732862673650649</td><td>No Hit</td></tr><tr><td>TTATCCGGCCAGGCGGGAACTGCAGTTCGGAGAGTGGCAGCGCAAAGACA</td><td>10</td><td>0.2277385561375541</td><td>No Hit</td></tr><tr><td>TTAACCTTCACCAGCGTGCGACCCTGGATCTGGTTATTAATGATGGCCTC</td><td>10</td><td>0.2277385561375541</td><td>No Hit</td></tr><tr><td>ATA</td><td>10</td><td>0.2277385561375541</td><td>No Hit</td></tr><tr><td>TTATCCAGATAGTTCGCCAGCTCTTCATTATTGAGTTTTTTCTTAAGCAC</td><td>9</td><td>0.20496470052379867</td><td>No Hit</td></tr><tr><td>TTAATTGGCATCAACACTGCAATCCTTGCGCCTGGCGGCGGGAGCGTCGG</td><td>9</td><td>0.20496470052379867</td><td>No Hit</td></tr><tr><td>TTATCCGGCGTGTAGGCATCGTCATGACGTAAACGGCGATCGGCGGTATA</td><td>8</td><td>0.18219084491004328</td><td>No Hit</td></tr><tr><td>ATCTACCGCGAAGGTTTTACCGGACTGGATCTGGCTTCGTCTGCCGCACA</td><td>8</td><td>0.18219084491004328</td><td>No Hit</td></tr><tr><td>TTAGGGATTAGCGTCTTAAGCTGGCGCGAGGACCAACGTATCAGCCAGGC</td><td>8</td><td>0.18219084491004328</td><td>No Hit</td></tr><tr><td>TTAA</td><td>8</td><td>0.18219084491004328</td><td>No Hit</td></tr><tr><td>ATC</td><td>8</td><td>0.18219084491004328</td><td>No Hit</td></tr><tr><td>T</td><td>7</td><td>0.15941698929628786</td><td>No Hit</td></tr><tr><td>TTT</td><td>7</td><td>0.15941698929628786</td><td>No Hit</td></tr><tr><td>TTATGGCTACTGGCGGTGCGGGTCGCGTTTATCGTTACAACACCAACGGC</td><td>7</td><td>0.15941698929628786</td><td>No Hit</td></tr><tr><td>TTATCCGGCGTTGCAACCTGTGAGCTGTAGATCATATCGGTGATAGCCTG</td><td>7</td><td>0.15941698929628786</td><td>No Hit</td></tr><tr><td>ATG</td><td>7</td><td>0.15941698929628786</td><td>No Hit</td></tr><tr><td>TTAAA</td><td>6</td><td>0.13664313368253245</td><td>No Hit</td></tr><tr><td>TTC</td><td>6</td><td>0.13664313368253245</td><td>No Hit</td></tr><tr><td>TTAGCATGACTCACGCCGGGCGTCCAGTTTTTAGCGACGGGGCACCCGAA</td><td>6</td><td>0.13664313368253245</td><td>No Hit</td></tr><tr><td>TTAGTGCGCTGGTTAGCGTGCGGGATAACGCCTGTCAGGATTATCTCGCG</td><td>6</td><td>0.13664313368253245</td><td>No Hit</td></tr><tr><td>TTATCCATCAGGGAGTTACTGTAAGCGAGAATATATTTATCACTCAATGC</td><td>6</td><td>0.13664313368253245</td><td>No Hit</td></tr><tr><td>ATAACCAGCATCAGCATTGGCGCGTAGAGAAAGGTAAAGCCCAGCAGCAA</td><td>6</td><td>0.13664313368253245</td><td>No Hit</td></tr><tr><td>TTATGCACCGCATCGTGAGCATCTTTCCCCCAGGCGAACGGCCCGTGCTG</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>TTATA</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>GT</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>TTAAGCTGCACCACACCGATACCGAGCGTAGTGGCAATACCGAAGATAGT</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>TTAAATACCGTCGGCGCGTTAATCGGCCCAACTGCGCCACCAACACCAAT</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>ATCA</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>TTGATCGTCAAAACCAACATTGCGACCGACGGTGGCGATAGGCATCCGGG</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>TTATATACCAGGCTTAGCTGGGGTTGCCCCTTAATCTCTGGAGAATAACG</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>TTGAGTTTCAGCAGCCGCGGTTCCGCCAGCACTTTACTGAAACTGCCTTT</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>ATCTACCGCGAGGTTAAGCTGCTGTTCAATCTGGGCGACGCTCAGTTCGG</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr></tbody></table></div><div class="module"><h2 id="M10"><img src="data:image/png;base64,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" alt="[OK]"/>Adapter Content</h2><p><img class="indented" 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pk6sXnDZDKZTCaTydSJzRsmk8lkMplMpk5s3jCZTCaTyWQydWLzhslkMplMJlMn1onNGyaTyWQymUydWCc2b5hMJpPJZDJ1Yp3YvGEymUwmk8nUiXVi84bJZDKZTCZTJ9aJzRsmk8lkMplMnVgnNm+YTCaTyWQydWKd2LxhMplMJpPJ1Il1YvOGyWQymUwmUyfWic0bJpPJZDKZTJ141048LbL6IZ2YyWQymUwmk3mXdeKnTlzbdHViJpPJZDKZTOa5O/FqIa4quzoxk8lkMplMJvPunfhDRERERORIqevEcQm2TsxkMplMJpPJvP46sU7MZDKZTCaTybx1J152WZ2YyWQymUwmk3n3Tjy77gSTyWQymUwm8z6duFRkXZ+YyWQymUwmk3mjdeJhrk7MZDKZTCaTydSJjTGTyWQymUwmUyc2xkwmk8lkMplMndgYM5lMJpPJZDJ1YmPMZDKZTCaTydSJjTGTyWQymUwmUyc2xkwmk8lkMplMndgYM5lMJpPJZDJ1YmPMZDKZTCaTydSJjTGTyWQymUwmUyc2xkwmk8lkMplMndgYM5lMJpPJZDJ1YmPMZDKZTCaTydSJjTGTyWQymUwmUyc2xkwmk8lkMplMndgYM5lMJpPJZDJ1YmPMZDKZTCaTydSJjTGTyWQymUwmUyc2b5hMJpPJZDKZOrF5w2QymUwmk8nUic0bJpPJZDKZTKZObN4wmUwmk8lkMnVi84bJZDKZTCaTqRObN0wmk8lkMplMndi8YTKZTCaTyWTqxOYNk8lkMplMJlMnNm+YTCaTyWQymTqxecNkMplMJpPJ1InNGyaTyWQymUymTmzeMJlMJpPJZDJ1YvOGyWQymUwmk6kTmzdMJpPJZDKZTJ3YvGEymUwmk8lk6sTmDZPJZDKZTKZOrBObN0wmk8lkMpk6sU5s3jCZTCaTyWTqxDqxecNkMplMJpOpE+vE5g2TyWQymUymTqwTmzdMJpPJZDKZOrFObN4wmUwmk8lk6sQ6sXnDZDKZTCaTqRPrxOYNk8lkMplMpk6sE5s3TCaTyWQymTrxCzrx9GNWb8w3XZ2YyWQymUwmk3nKTvxYZFff14mZTCaTyWQymVfuxKUWu1wz1omZTCaTyWQymVfuxMs9Em2d+ENERERE5EjJduLHPRKl/RLWiZlMJpPJZDKZd9k7oRMzmUwmk8lkMnVinZjJZDKZTCaTeePrTpS2FLvuBJPJZDKZTCbz+p3Y9YmZTCaTyWQymbfuxCNdnZjJZDKZTCaTqRMbYyaTyWQymUymTmyMmUwmk8lkMpk6sTFmMplMJpPJZOrExpjJZDKZTCaTqRMbYyaTyWQymUymTmyMmUwmk8lkMpk6sTFmMplMJpPJZOrExpjJZDKZTCaTqRMbYyaTyWQymUymTmyMmUwmk8lkMpk6sTFmMplMJpPJZOrExpjJZDKZTCaTqRMbYyaTyWQymUymTmyMmUwmk8lkMpk6sTFmMplMJpPJZOrExpjJZDKZTCaTqRMbYyaTyWQymUymTmzeMJlMJpPJZDJ1YvOGyWQymUwmk6kTmzdMJpPJZDKZTJ3YvGEymUwmk8lk6sTmDZPJZDKZTCZTJzZvmEwmk8lkMpk6sXnDZDKZTCaTydSJzRsmk8lkMplMpk5s3jCZTCaTyWQydWLzhslkMplMJpOpE5s3TCaTyWQymUyd2LxhMplMJpPJZOrE5g2TyWQymUwmUyc2b5hMJpPJZDKZOrF5w2QymUwmk8nUic0bJpPJZDKZTJ1YJzZvmEwmk8lkMnVindi8YTKZTCaTydSJdWLzhslkMplMJlMn1onNGyaTyWQymUydWCc2b5hMJpPJZDJ1Yp3YvGEymUwmk8nUiXVi84bJZDKZTCZTJ9aJzRsmk8lkMplMnVgnNm+YTCaTyWQydeJdO/H0dZ4K7urtOjGTyWQymUwm82qdeLPg6sRMJpPJZDKZzDt24uWasU7MZDKZTCaTybxsJ17dI9HWiT9ERERERI6UVCd+Kr6l/RLWiZlMJpPJZDKZl10nLpVanZjJZDKZTCaTqRPrxEwmk8lkMpnMe3Tipz3Eq1uKXXeCyWQymUwmk3nxdWLXJ2YymUwmk8lk2jsxztWJmUwmk8lkMpk6sTFmMplMJpPJZOrExpjJZDKZTCaTqRMbYyaTyWQymUymTmyMmUwmk8lkMpk6sTFmMplMJpPJZOrExpjJZDKZTCaTqRMbYyaTyWQymUymTmyMmUwmk8lkMpk6sTFmMplMJpPJZOrExpjJZDKZTCaTqRMbYyaTyWQymUymTmyMmUwmk8lkMpk6sTFmMplMJpPJZOrExpjJZDKZTCaTqRMbYyaTyWQymUymTmyMmUwmk8lkMpk6sTFmMplMJpPJZOrE5g2TyWQymUwmUyc2b5hMJpPJZDKZOrF5w2QymUwmk8nUic0bJpPJZDKZTKZObN4wmUwmk8lkMnVi84bJZDKZTCaTqRObN0wmk8lkMplMndi8YTKZTCaTyWTqxOYNk8lkMplMJlMnNm+YTCaTyWQymTqxecNkMplMJpPJ1InNGyaTyWQymUymTmzeMJlMJpPJZDJ1YvOGyWQymUwmk6kTmzdMJpPJZDKZTJ3YvGEymUwmk8nUiXVi84bJZDKZTCZTJ9aJzRsmk8lkMplMnVgnNm+YTCaTyWQydWKd2LxhMplMJpPJ1Il1YvOGyWQymUwmUyfWic0bJpPJZDKZTJ1YJzZvmEwmk8lkMnVindi8YTKZTCaTydSJdWLzhslkMplMJlMnfk0nnr7P8pbl7Toxk8lkMplMJvNGnbi26erETCaTyWQymcyzduIfuuxjoy31Y52YyWQymUwmk3nBTry6HtzWiT9ERERERI6UN3Ri68RMJpPJZDKZzPOtE5d6sE7MZDKZTCaTybxRJ36KTsxkMplMJpPJvFcnDhqt604wmUwmk8lkMnVi1ydmMplMJpPJZN6sEw9wdWImk8lkMplMpk5sjJlMJpPJZDKZOrExZjKZTCaTyWTqxMaYyWQymUwmk6kTG2Mmk8lkMplMpk5sjJlMJpPJZDKZOrExZjKZTCaTyWTqxMaYyWQymUwmk6kTG2Mmk8lkMplMpk5sjJlMJpPJZDKZOrExZjKZTCaTyWTqxMaYyWQymUwmk6kTG2Mmk8lkMplMpk5sjJlMJpPJZDKZOrExZjKZTCaTyWTqxMaYyWQymUwmk6kTG2Mmk8lkMplMpk5sjJlMJpPJZDKZOrF5w2QymUwmk8nUic0bJpPJZDKZTKZObN4wmUwmk8lkMnVi84bJZDKZTCaTqRObN0wmk8lkMplMndi8YTKZTCaTyWTqxOYNk8lkMplMJlMnNm+YTCaTyWQymTqxecNkMplMJpPJ1InNGyaTyWQymUymTmzeMJlMJpPJZDJ1YvOGyWQymUwmk6kTmzdMJpPJZDKZTJ3YvGEymUwmk8lk6sTmDZPJZDKZTCZTJzZvmEwmk8lkMnVindi8YTKZTCaTydSJdWLzhslkMplMJlMn1onNGyaTyWQymUydWCc2b5hMJpPJZDJ1Yp3YvGEymUwmk8nUiXVi84bJZDKZTCZTJ9aJzRsmk8lkMplMnVgnNm+YTCaTyWQydWKd2LxhMplMJpPJ1In37sTTQzK368RMJpPJZDKZzEt14mUPXr6vEzOZTCaTyWQyL75OvFpqg66sEzOZTCaTyWQydeJiPkREREREjpSKTrzcN2ydmMlkMplMJpNpnVgnZjKZTCaTyWTqxDoxk8lkMplMJvMOndh1J5hMJpPJZDKZ1oldn5jJZDKZTCaTae/EQFcnZjKZTCaTyWTqxMaYyWQymUwmk6kTG2Mmk8lkMplMpk5sjJlMJpPJZDKZOrExZjKZTCaTyWTqxMaYyWQymUwmk6kTG2Mmk8lkMplMpk5sjJlMJpPJZDKZOrExZjKZTCaTyWTqxMaYyWQymUwmk6kTG2Mmk8lkMplMpk5sjJlMJpPJZDKZOrExZjKZTCaTyWTqxMaYyWQymUwmk6kTG2Mmk8lkMplMpk5sjJlMJpPJZDKZOrExZjKZTCaTyWTqxMaYyWQymUwmk6kTmzdMJpPJZDKZTJ3YvGEymUwmk8lk6sTmDZPJZDKZTCZTJzZvmEwmk8lkMpk6sXnDZDKZTCaTydSJzRsmk8lkMplMpk5s3jCZTCaTyWQydWLzhslkMplMJpOpE5s3TCaTyWQymUyd2LxhMplMJpPJZOrE5g2TyWQymUwmUyc2b5hMJpPJZDKZOrF5w2QymUwmk8nUic0bJpPJZDKZTKZObN4wmUwmk8lkMnVi84bJZDKZTCZTJ9aJzRsmk8lkMplMnVgnNm+YTCaTyWQydWKd2LxhMplMJpPJ1Il1YvOGyWQymUwmUyfWic0bJpPJZDKZTJ1YJzZvmEwmk8lkMnVindi8YTKZTCaTydSJdWLzhslkMplMJlMn1onNGyaTyWQymUydeO9OPD0kc7tOzGQymUwmk8m8VCd+bLFP9ffL+zoxk8lkMplMJvPi68SrpXa5ZqwTM5lMJpPJZDJ14u18iIiIiIgcKdWdeHXjhHViJpPJZDKZTOZd1onjEqwTM5lMJpPJZDIv3omXXVYnZjKZTCaTyWTeqBOXiqzrTjCZTCaTyWQyb9GJp0VWP6QTM5lMJpPJZDKvvE480tWJmUwmk8lkMpk6sTFmMplMJpPJZOrExpjJZDKZTCaTqRMbYyaTyWQymUymTmyMmUwmk8lkMpk6sTFmMplMJpPJZOrExpjJZDKZTCaTqRMbYyaTyWQymUymTmyMmUwmk8lkMpk6sTFmMplMJpPJZOrExpjJZDKZTCaTqRMbYyaTyWQymUymTmyMmUwmk8lkMpk6sTFmMplMJpPJZOrExpjJZDKZTCaTqRMbYyaTyWQymUymTmyMmUwmk8lkMpk6sTFmMplMJpPJZOrE5g2TyWQymUwmUyc2b5hMJpPJZDKZOrF5w2QymUwmk8nUic0bJpPJZDKZTKZObN4wmUwmk8lkMnVi84bJZDKZTCaTqRObN0wmk8lkMplMndi8YTKZTCaTyWTqxOYNk8lkMplMJlMnNm+YTCaTyWQymTqxecNkMplMJpPJ1InNGyaTyWQymUymTmzeMJlMJpPJZDJ1YvOGyWQymUwmk6kTmzdMJpPJZDKZTJ3YvGEymUwmk8nUiXVi84bJZDKZTCZTJ9aJzRsmk8lkMplMnVgnNm+YTCaTyWQydWKd2LxhMplMJpPJ1Il1YvOGyWQymUwmUyfWic0bJpPJZDKZTJ1YJzZvmEwmk8lkMnVindi8YTKZTCaTydSJdWLzhslkMplMJlMn3rUTTz9mteAGH9WJmUwmk8lkMpmXWicudeLapqsTM5lMJpPJZDKv04mfbkmWXZ2YyWQymUwmk3n3TvwhIiIiInKkWCdmMplMJpPJZFon1omZTCaTyWQymTqxTsxkMplMJpPJ1IkbO/HsuhNMJpPJZDKZzJt04unrPBVc1ydmMplMJpPJZN5lnXiYqxMzmUwmk8lkMnViY8xkMplMJpPJ1ImNMZPJZDKZTCZTJzbGTCaTyWQymUyd2BgzmUwmk8lkMnViY8xkMplMJpPJ1ImNMZPJZDKZTCZTJzbGTCaTyWQymUyd2BgzmUwmk8lkMnViY8xkMplMJpPJ1ImNMZPJZDKZTCZTJzbGTCaTyWQymUyd2BgzmUwmk8lkMnViY8xkMplMJpPJ1ImNMZPJZDKZTCZTJzbGTCaTyWQymUyd2BgzmUwmk8lkMnViY8xkMplMJpPJ1InNGyaTyWQymUymTmzeMJlMJpPJZDJ1YvOGyWQymUwmk6kTmzdMJpPJZDKZTJ3YvGEymUwmk8lk6sTmDZPJZDKZTCZTJzZvmEwmk8lkMpk6sXnDZDKZTCaTydSJzRsmk8lkMplMpk5s3jCZTCaTyWQydWLzhslkMplMJpOpE5s3TCaTyWQymUyd2LxhMplMJpPJZOrE5g2TyWQymUwmUyc2b5hMJpPJZDKZOrF5w2QymUwmk6kT68TmDZPJZDKZTKZOrBObN0wmk8lkMpk6sU5s3jCZTCaTyWTqxDqxecNkMplMJpOpE+vE5g2TyWQymUymTqwTmzdMJpPJZDKZOrFObN4wmUwmk8lk6sQ6sXnDZDKZTCaTqRPrxOYNk8lkMplMpk68dyeeHqITM5lMJpPJZDJv2olrG61OzGQymUwmk8m8Tid+arGdtXj56X/43Z//9Ou/r7z96m9Pb9/+7F//+cl///Hzfz5/aPG53/78uyO//Xwkk8lkMplMJvPM5g9vf/z9Xy7ViT8W+eaXf/3u3rx58+bNmzdv3rx5K7x986u/fuyWN3TiZT63/j/95u+Zt29/8c///PS/n//rSEc60pGOdKQjHenImxz5w9vV1olFRERERM4SnVhEREREdOK1HqwQi4iIiMh9O/Go6xOLiIiIiJyyE+91HzU9O9/Laxv85pHT1xnyvKZFXvncg2M2hZ7PPcK9bx4ZC6ufWzVDSkdmhPjeO7+OOu+99gukZ+zGfr2/4N43X6LMnO+ZdaXxbf6arV0laZ518b1XTdoAGf65R7h357q3n+v6v3MN/G7Y/ODHfkU3PKPN21+wYvu69eDk2Tz/ZdyAb57X2p5O1TeM/mf0+ERqX9XO17nhle8RSl8bmbvefI7xV2zzq735HDe1+PVpGPHSXC2dZDN31/AVl5918ef233tm8rTNgYa2PeSlzo918sut7c9LMjMt+UXX+VKsPt/8DxU9L0Kn8Pi5bbOu+Vw3N+2fDB5n5lwXHFP7ZZ4879V+XTeUsPjU2vBzS5W5R2ts+JJsblxtM+Ganbj/DBgfMKoTt41Q53ltYCttbupDDujsxEOGLDMfer5P7PE9sv/raPjJvecrbvND/dOyreT1f27b8xpYBBumUP+5sfPHp9d8O9j1ZNj/o8WQWVd1rhvSiZvPdfv9/D/q1Drqe33PGNWaR+jEPY1LJ969pOZ/2s7/pmxu+q2iTnyETlx77nhauWn7hdpxOnHt7yV7Br1havWv3GTWTqruvfZ3OKXfI2fWzHp+E1oa3/z3/uB3l/mfglbvfXP/QPIYnbjqFNH8W6naWXfMTlw1o97ViZt/B9U/djt14s7fqtk70bVykNzt1HBWze9eGLgQkt+7lr/3nhWghh1Oya+ZhrNt2ys/di0hOUNKr1JDu+ppBvEegIZ7n+t//9vcPNr2pMbflTN74Fa/abXNuuafxHo2hq6+n/ySLN1Lw2+xN9+v+rp+YyHu/Bmyaldu87mu+SexOb3j2aw7Syeu/T51/E68xzM6WSceWKCb99kM3808cDnw8RQ2cOVjs8MN+Taz+dNt/lvU2M21tSflgfsL8x104N6JhnvvXOvanHXJudfw9Z557vHxVbMubtg9P3s0nJdqn/u852+xG+593mcDyR5f78mXMXnvyVmXeeVLs27I3w+sgsnn3vBgXnPvr+nE+TND829NX9yJe57RqNZxtU48dpdF89+QvnL3wjxup+yon8Ze34lfdu/5v2QfPqUPtZ94p3uPX+Eh12lp+HrPr6n03HvwyjdcPmLvTtxQ5gZ24rH3fudzXfJ36Hv/Te0Nz3UDV4Iavh8dthN3fofViQccNgSv/bv45JHDvyBrV757tkkd8LoTu34Py79ozddFOch1J9q+R3b+AmfUpV3euLOz/xzSc7WT5vNS1S7ttt9iJ+89s5N7bCe+/LmuZ19scv2y83IlbRcbabhWVdX36P57b5uHzYvxSbPhWis7/bS5x9/YXWHvRNsFegdezbfqpDb86sgNG0AbNqpWvfLJ9YOeq052CpnP7Vmt3Pya3O+Kof3X7HzLvc/dv8CpXSvtvD5xp9A265Jze49RM+v2WPvvP893Lpida9a1Pff4rl9/73Pfrome73qjzD2uT9xwZhj498QX/Bs7EREREZFjRicWEREREZ1YREREREQnFhERERHRiUVEREREdGIREREREZ1YREREREQnFhERERHRiUVEREREdGIREREREZ1YRESudaIP/5HV+JjA3PvfWRUR0YlFRKpr32M6u+OTMKT8vbFBBp245+HpxCKiE4uIHK4TD6xrF2t7OrGIiE4sInfvxKX14+WNP7y/PH5Te/rE+BHmD356DPGzCG5fvZfk8bGjFouITiwicoJOvKyVqzW39E5e21xzrT14WUzjZ5F5nJuduOpp6sQiohOLiByuEwcruEH9zXy0+fb+g/OfstNdtD0SERGdWETkPZ04c/vqroBTdOKqvQ06sYiITiwiOnFdh6vaO/GuTlz17HRiERGdWER04q9uf81+4r078eZ6dn4T8Oq9NOwnVohFRCcWETlHJ57rrzux/FDyuhP7deLks8hfLyJ+XklHJxYRnVhERK7wg8Rmr80swIuI6MQiInLx3uxFEBGdWEREdGIREZ1YREREREQnFhERERG5dv4PnFebX541r0cAAAAASUVORK5C" alt="Adapter graph" width="945" height="600"/></p></div></div><div class="footer">Produced by <a href="http://www.bioinformatics.babraham.ac.uk/projects/fastqc/">FastQC</a>  (version 0.11.8)</div></body></html>
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+</style></head><body><div class="header"><div id="header_title"><img src="data:image/png;base64,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" alt="FastQC"/>FastQC Report</div><div id="header_filename">Thu 24 Feb 2022<br/>test.fastq2_5pAtccRm.fq</div></div><div class="summary"><h2>Summary</h2><ul><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M0">Basic Statistics</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M1">Per base sequence quality</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M2">Per tile sequence quality</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M3">Per sequence quality scores</a></li><li><img src="data:image/png;base64,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" alt="[FAIL]"/><a href="#M4">Per base sequence content</a></li><li><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAEkklEQVR42s2XV2hUaxSF/4nRiaIoiKA+CDYMdsQnS8CAFREVsV4VUR9sWMECVuzYsETsGnvvivVaImhyU+Hq9VUfzKtKkptk5nz3rPkz42RyJskE5Xpgw8yZ8++1Zu+1yzGA+T8t8UPGJP1lTGquMenZxvwh02fd02+/jECOMSNdoEwX6KtrgQJjSv425rtMn3VPv+kZPfvTCLj/MM11WphnTNnnlJRA6fDhsGkTHDsG16/D2bOwfj3OtGmUDhjAZ78/oGd1RmcbTOBPY5JdRxmuo/IvyclBZ/lyeP8ePn6EoiLIyYE3b+D5c3j4EG7fhitXICMDZ8QIiv3+oM7Kh3wlRCDfmFbuwawiY0orOnWCmzfhwwcoLITsbMjKgmfP4MEDuHULLl+2kTh+PESAvXth7Voq+/RBPuRLPutFoOqfZ/1jzL8KK3l5UFAA797B69fw9Cncv29JXboEmZk2HYcOwZ49sG0bbNwIa9aAGzWnd2/kSz69IlGDgEIm1s6UKZCfD2/fwqtX8OQJ3LsHN27AxYtw5gwcPQoHDsDu3bB1K2zYAKtXw7JlsHAhzJ0LM2fipKaGI5FRK4EqwZVXtGtnc/viBTx+DHfvWsFduACnT8ORI7B/P+zaBVu2hETIqlUWeMECmDMHZsyASZNg3DgYNYrK1q2R71hhViMg5X4xJsjOnfDoEdy5A9euwfnzcOqUTUNurgXevBnWrYOVK2HJEli0yGpDaZk4EcaOhZFuNaanw6BB0KsXxT6fhFnoSUC1q/Jxhg61ir56Fc6dg5Mn4fBhq/jKSggE7GcBL14M8+bZUEsfwSCUl8OJEzBkCAwcCP37h8Dp1g2nZUuEEd0nov995iefLxASVKyiX76Eigoil4jouY4doUcPmyIRC18isW8fdO8OXbpA27bgguP388ltWMKqTsC2168lXbtWV/T27bBihRWdQKMvERI5kY0G16XvSllSkoWIsm+uCSvctkME1MfVShkzxipapSRFz54NzZtbR1J7LIlwSmLBVZrJyTXAZY4lEAjNjjABDRP1c6ZO/aHoCROgSZMfh+OR8AJv3NgTPGzCEmaEgCaahgrTp8PSpaAe0KhRzcMicfCgNwmBKx11gMuEJcyaBAQ8axa0aeN9WGFVbmPDHk6HNOHzJU4gkgKVYN++iYNHC1PirYNEjRREROi2TM/QxwPXd6/qkJDjkPAUYbgMv3kdUt7VjOKVmpcmRELd0sOfZxlGGpGi4BU2db2ysprgioxXdZSW2qEU6yclJU4jimrFwXi5C5OIBvcqUYGrjGNTOHgwTufO8VtxtWFUGwmlw6vJiIQmZCx4ixa2p7glXrUlFdY5jstrKyOP9hqx2Jx36ADz54fGdEV9xnH0QhKso5api2Ramu2q7qISdENfr4UkdiVrEIlWrex4Vim6Y9xxR3JCK1nsUlpeX2BX4dp8Qo1IE9XVQ2W/fokvpZ5ruSvMYLxQaycYPRp27Ij0BWfyZIqbNm34Wh7vxUQ1/L1ZM5z27aFnT0LTUwNs/HicYcMoce9pqfkpLya/zavZb/Ny+qvsPyB3ge/Rlc06AAAAAElFTkSuQmCC" alt="[FAIL]"/><a href="#M5">Per sequence GC content</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M6">Per base N content</a></li><li><img src="data:image/png;base64,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" alt="[WARNING]"/><a href="#M7">Sequence Length Distribution</a></li><li><img src="data:image/png;base64,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" alt="[PASS]"/><a href="#M8">Sequence Duplication Levels</a></li><li><img src="data:image/png;base64,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" alt="[FAIL]"/><a href="#M9">Overrepresented sequences</a></li><li><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAFlUlEQVR42s2XCUzTVxzHybIs0IgCLYqyQ9RtmhjCNKKbikajYVc22NThNjYjeC0yWBESxAV1Ckw8QEUF5ChnS4FyFETucwWU+7ClHKKiImLI4nCz9bv3/pS7ra1HtM1Lm/b/fp/ve+93PQMABq9y6D/Bz+ANNvethWxPw3Xs3wx/YAb9Tn6j/700AeZc1qccrhGPw2UNkk8Fx9voIceX9Tcz6Hf62/B/PPrsCxNgzjW043iyGjheRkOWQRzFt2IH/Nl4DDFyHjJ6siDoSoZ/YwB2VuyEffpGzA5iK+izdA6d+8wCyHa+SYyEsj2N/jU/aaL0vbIf0sF2tA92oOVBG+ruN6CqrwZldypR0FuMnBuXkX49C5GyaGwq3ASLU2ZKOpfaoLb0EmDibmLC8TQq5/iw/vlIaA1xjxiyQTmaH7Sitr8ekr5qlN6pQP6tImTfyIXoeiYEnSmIlSfiooyHc20R8G84htUZq0FtUFvUpk4ChldO4H6sRzvKXdEw0ISmgRZc7a/DXwRccrscebcKIb5xCWndGeB3CsGTJyBCGoPQtnCcajlLjugk/qgPxO+1h7Eqyw7UFrWpbiemCKBbRlW7lrmgcaAZV/prUXm3CsW3y3D5VgGyenKQ2p2OpM5k8NoTEC6Nxtm2MJxsPoPAxhM4XB+AA1cPwbvmADyqvPFLpQdsM1aodoIVqlUAdRp6bgv5HzBbXHFXgqLbpci9mY/MnmykdIuQ2CFATHs8wqRRONN6ASeaTyOg8TgO1fnDl4C9anzhLvHCnkp3uJTvgXOJC7YUOWN+0nww/jTJMSevvsHs+DRlSOsZFPaW4NLNPOLpYgi70pBAwFHtcbhwLRKnW8/jeHMIOecgHKw7iv1XD2Jf9X78KtmHyNZoiOQi/FiyHZsJ+Ov87/DZZUesEq8H+4SxkjLUCmDinISPY74jcm4Oe3RyVyriO/iIksUS8EWEtJ5DUFMwjhIH86s7Ap8rfvCs9oGbxBO7KtwQ3hKBrgdd6H94D3ypgIAdsD7nc6wWb8DyzDWYy58HyhifJ8ZWT5NMoLGCJ48jsZ2COHkSCSkezl+LQHBLKI40BGJLsRPW5qzDskxbLE5bDBuRDWwzV5DV2SGwNhCdAx0Yed172AdeWyyWpa/ColQbzE1+H7MTLcEOmKagrAkCaAqlWWwZf6kqlMY8+gDZ3jXZazEz0Rym8TPUDg+yetl9Kca/HikeIUUmgEXizAnPml2YDsoaSduMAJrHaSrdWvw9AYcR8LBHu0m4eJtvqRGsDS4k8DlJFlPnxM0AZVHmmABSTGg+31GxW+XRAfi51AWztKxaI/zxELNytXDVoCzKHBNAKhotKrsr9zIe7Vq+G5wEs9EJi1I+hFDKx7zkuTrAk7XCGQGERZlTBLiSuN1Ltn2BcMEEeGF3PoaI8dzObFgJ3nsuuHoBqiNwLNgMu+x1ow9SByrsyoNC+ZiBPFb8h5LrhWrhqTKhTnD1R6BywuWZn0zYejq2FTuj/k7tKEz5RPlccLVOOBKG7DATtZO+yXNATW81npD3ZHhaux5wTWE4kohoktA0cWPOelT3SkZFDMNT9ICbwCJplvpEND4Vm8ZqNrJBJWJIT7h5Ioek5a+wRLRUcyoeX4y0GaMiaEjqCn9X8A62le0ADXGLYLbmYjS+HJtGTdf5TLUNa5E1Kc8+8K09iPkJVk8vx+MbEm1H8bTBTjDFF3lfMlmVNipLREt0a0gmt2TPIsKKZEv3Ki5TU2gZt8+1168lm9yU6noc1MO3FDkxYNojhpH+YW2Gnf5Nqbq2nHHMWPVbbZNuA6firQghpZt2TRHSSGwn/eScYPNnb8s1XUxoDFtGWpD6sAgrxSvhSi4juypJ31f6ExwLSNsl/BicAOMXczF5ba5mr83l9GWN/wE1f784zfWjGwAAAABJRU5ErkJg" alt="[PASS]"/><a href="#M10">Adapter Content</a></li></ul></div><div class="main"><div class="module"><h2 id="M0"><img src="data:image/png;base64,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" alt="[OK]"/>Basic Statistics</h2><table><thead><tr><th>Measure</th><th>Value</th></tr></thead><tbody><tr><td>Filename</td><td>test.fastq2_5pAtccRm.fq</td></tr><tr><td>File type</td><td>Conventional base calls</td></tr><tr><td>Encoding</td><td>Sanger / Illumina 1.9</td></tr><tr><td>Total Sequences</td><td>4391</td></tr><tr><td>Sequences flagged as poor quality</td><td>0</td></tr><tr><td>Sequence length</td><td>1-127</td></tr><tr><td>%GC</td><td>52</td></tr></tbody></table></div><div class="module"><h2 id="M1"><img src="data:image/png;base64,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" alt="[OK]"/>Per base sequence quality</h2><p><img class="indented" 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" alt="Per base quality graph" width="1020" height="600"/></p></div><div class="module"><h2 id="M2"><img src="data:image/png;base64,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" alt="[OK]"/>Per tile sequence quality</h2><p><img class="indented" src="data:image/png;base64,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" alt="Per base quality graph" width="1020" height="600"/></p></div><div class="module"><h2 id="M3"><img src="data:image/png;base64,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" alt="[OK]"/>Per sequence quality scores</h2><p><img class="indented" src="data:image/png;base64,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" alt="Per Sequence quality graph" width="800" height="600"/></p></div><div class="module"><h2 id="M4"><img src="data:image/png;base64,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" alt="[FAIL]"/>Per base sequence content</h2><p><img class="indented" 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itLl6pk/+67iYT+mTPd/ovOgYmJiYmJiYmJGcBn+lNTGTr0X5w8WY3had48kdA/f74K/SEhdA5MTExMTExMTExCv45D//n+/dW8nN27ezaHY8kSFfrffpvOgYmJiYmJiYmJSejXceg/266dCv1DhyYS+letchvuT+fAxMTExMTExMQMpNCftpVxQ/+pevUk2dunT08k9P/6qwr9r75K58DExMTExMTExLwHzbQM53c39DvefFOSvWPlykRC/+bNKvQXK0bnwMTExMTExMTEJPTrOPRbixSRZO/880/P5nD+8Yeawv+ZZ+gcmJiYmJiYmJiYhH4dh37Tgw+q0H/8eCKhf88eFfqfeILOgYmJiYmJiYmJSejXa+iPu3ZNYr0he/ZEm8N58KAK/Y8+SufAxMTExMTExMQk9Os19EebzW7n8m+r48fVW4LcuekcmJiYmJiYmJiYhH69hv7ru3a5zc9zW5lMKvTfdx+dAxMTExMTExMTk9Cv19B/ZfVqdfmtKlUSbw+HQ4X+TJnoHJiYmJiYmJiYmIR+vYb+/6ZPV6G/ceOkWsSYLZv6mq/VSufAxMTExMTExMQk9Osy9F8YMkQyveXzz5MM/blyqdB/8iSdAxMTExMTExMTk9Cvy9B/rnNnyfS2b75JMvTny6dC/5EjdA5MTExMTExMTExCvy5D/+lGjSTT27//PsnQX6CACv1//03nwMTExMTExMTEJPTrMvQ7g4Ml0zuWLEmqRUxPP60W2LmTzoGJiYmJiYmJiUno12Xot730ksr0W7YkGfqff14tsH07nQMTExMTExMTE5PQr8vQb374YTV65/DhJEP/yy+r0P/bb3QOTExMTExMTExMQr/+Qn9cdLQhUyZDlixhDkdSLWIuU0YN+l+zhs6BiYmJiYmJiYlJ6Ndf6I8JC1OT9OfP76VFzG+8oUL/smV0DkxMTExMTExMTEJ/2oT+IJfy5fHUhP7r+/er+TpLlPAW+t95R4X+hQvpHJiYmJiYmJiYmIT+NAj9nkHf83Yahv6rGzaoAf1VqngL/VWrqtA/Zw6dAxMTExMTExMTk9CfjqHfy5uB1IT+S/PmSaA/3ayZlxax1K6tPg2YNo3OgYmJiYmJiYmJSejPcKF/bXIV+sknEuh3163rZZm/4yfy/71797UURVEURVEURXktn0L/zSTG7qfTmf7wHj0k0EcMH+7tTH+TJupM/+jRvCPExMTExMTExMTkTL/+hvecad5cAv2l2bO9tIi1ZUtZxjpkCJ0DExMTExMTExOT0K+/0B9WvboE+qu//OIt9Ldtq0L/gAF0DkxMTExMTExMTEJ/Oob+m+kze4+9ZEkJ9Nf37fMW+jt1UqG/Tx86ByYmJiYmJiYmJqE/DUL/zTs7T7+lYEEJ9NF2u7fQ3727Cv3du9M5MDExMTExMTExCf1pE/rT0vUe+uPijFmzSqCPi4ry0iK2r76SZSwdO9I5MDExMTExMTExCf06C/0x4eGS5k358nlvINs336jQ36YNnQMTExMTExMTE5PQr7PQH3X0qBq3U7RoMqF/2DAV+lu0oHNgYmJiYmJiYmIS+nUW+q9t3Spp3lmxovcGso8ZI4uZGzemc2BiYmJiYmJiYhL6dRb6Ly9aJGn+dIMGyYT+SZNU6K9Xj86BiYmJiYmJiYlJ6NdZ6L84YYKk+XMdOyYT+qdPV6G/Vi06ByYmJiYmJiYmJqFfZ6H//NdfS5q/MGhQMqF/7lwV+qtWpXNgYmJiYmJiYmIS+nUW+s9++qmk+f+mTfPeQI74UUCmihXpHJiYmJiYmJiYmIR+nYX+U3XqSJq/smJFMmf6ly9Xob9cOToHJiYmJiYmJiYmoV9nod9Rrpyk+cjQ0GTO9K9bp0J/qVJ0DkxMTExMTExMTEK/zkK/pXBhSfM3jEbvDeTctEkWM770Ep0DExMTExMTExOT0K+z0G+8/35J87GXLycT+n//XYX+556jc2BiYmJiYmJiYhL69RT6JeurKH///ck2kHPXLrXkU0/ROTAxMTExMTExMQn9egr9NwwGifLWZ55JPvTv369Cf/78dA5MTExMTExMTExCv55Cf2RoqER5R7lyyTfQ0aOypCFvXjoHJiYmJiYmJiYmoV9Pof/KihUS5U/VqZP8mf74zwSM999P58DExMTExMTExCT06yn0/zd1qkT5s23aJN9Adrs6058lC50DExMTExMTExOT0K+n0H/hm28kyp/v29eXBpLELwtL+qdzYGJiYmJiYmJiEvp1E/rPdewoOf7ihAk+hf6cOVXoNxrpHJiYmJiYmJiYmIR+3YT+0x9+KDn+8uLFPoX+PHlU6D92jM6BiYmJiYmJiYlJ6NdN6HdUqCA5/tq2bb40kDF/flnYuX8/nQMTExMTExMTE5PQr5vQby1aVHJ81NGjPoX+p55SoX/XLjoHJiYmJiYmJiYmoV83od+UN6/k+Njz530K/UWKqNC/YwedAxMTExMTExMTk9Cvj9AfFxWlpt7Plu1mXJxPob9YMRX6N22ic2BiYmJiYmJiYhL69RH6o+On3rcULOhjA5lKlVKX7123js6BiYmJiYmJiYlJ6NdH6L++d6+EeHupUr6G/nLlVOhfsYLOgYmJiYmJiYmJSejXR+i/um6dmoKzRg1fQ3/8VD+OxYvpHJiYmJiYmJiYmIR+fYT+S7NnS4g/07y5jw1krlJFfTIwdy6dAxMTExMTExMTk9Cvj9AfMXy4hPjwnj19Df21aqnQP306nQMTExMTExMTE5PQr4/QH96tm4T4iFGjfA399eqp0D95Mp0DExMTExMTExOT0K+P0H+6WTMJ8ZfmzfM19DdqpEL/2LF0DkxMTExMTExMTEK/PkK/M36M/tUNG3xsIEvz5rK8bdgwOgcmJiYmJiYmJiahXx+h31a8uIT4qAMHfA39bdqo0P/NN3QOTExMTExMTExMQr8+Qr85f34J8TEuv20yob9jRxX6v/6azoGJiYmJiYmJiUno10Poj401ZMliyJQpLjraxwayfvGFhH5rjx50DkxMTExMTExMTEK/DkJ/zJkzkuDNjzziewNZe/dWob9TJzoHJiYmJiYmJiYmoV8HoT/q0CE1Vufll/0I/QMGqNDfti2dAxMTExMTExMTk9Cvg9B/bdMmSfDO4GA/Qv+QISr0t2pF58DExMTExMTExCT06yD0X/7xR0nwpxs39r2BbKNGySqWpk3pHJiYmJiYmJiYmIR+HYT+iDFjJMGf69LFj9A/YYIK/fXr0zkwMTExMTExMTEJ/ToI/eHx38q9MGSIH6F/2jQV+mvXpnNgYmJiYmJiYmIS+nUQ+s+0aiUJ/r8ZM3xvIPucOWrCn2rV6ByYmJiYmJiYmJiEfh2E/rCaNSXBX12zxo/Q/9NPKvRXqkTnwMTExMTExMTEJPSnNvQHeVSi/5Wa0G8vW1YS/PVdu/wI/UuXqtD/xht0DkxMTExMTExMTEJ/Gp/pdwv9XqK876Hf8tRTkuCjLRY/Qv+aNSr0lylD58DExMTExMTExCT0p2XoTzTx+5X7E13MeN99kuDjIiN9byDHb7/JKqZXXqFzYGJiYmJiYmJiEvozVuhf61G/LF4s8f3fnDnX+lO/ff+9rHW0UKG1FEVRFEVRFEUlXf6Ffu8pP8Vn+m+cOKGurfvcc369K3KEhqoz/U8/zTtCTExMTExMTExMzvSn2Zn+dAr9kb//LvHd8dZbfjWQ8++/ZS1jgQJ0DkxMTExMTExMTEJ/2oR+z7CeVqH/Svw8PKfq1fMv9B85okL/Qw/ROTAxMTExMTExMQn96RX6b6bR7D0XJ0+W+H62XTv/Qv+//6rQ/8ADdA5MTExMTExMTExCfxqE/qQyfZrM03++f3+J7+cHDPCvgaxWFfqzZaNzYGJiYmJiYmJiEvrT5kx/mrkeof/a9u2S+OWnvw1kyJRJcn+Y00nnwMTExMTExMTEJPRn6NCf4gYyxM/uH2Y20zkwMTExMTExMTEJ/YEZ+o25c0vodx4/TufAxMTExMTExMQk9Ado6H/kERX6Dx6kc2BiYmJiYmJiYhL6AzT0P/GECv179tA5MDExMTExMTExCf0BGvqfeUaF/j//pHNgYmJiYmJiYmIS+gMz9JtefFFdynfLFjoHJiYmJiYmJiYmoT9AQ3+JEir0//ornQMTExMTExMTE5PQH6Ch/7XXVOhftYrOgYmJiYmJiYmJSegPzNBvfvttCf32JUvoHJiYmJiYmJiYmIT+AA39lSur0L9gAZ0DExMTExMTExOT0B+gof/dd1XonzmTzoGJiYmJiYmJiUnoD9DQ//77KvRPmULnwMTExMTExMTEJPQHZui3NGwood82bhydAxMTExMTExMTk9AfoKH/o49U6B85ks6BiYmJiYmJiYlJ6A/Q0N+6tQr9335L58DExMTExMTExCT0B2bot3boIKHf2rcvnQMTExMTExMTE5PQH6Chv2tXFfq//JLOgYmJiYmJiYmJSegP0ND/5Zcq9HftSufAxMTExMTExMQk9Ado6O/XT4X+9u3pHJiYmJiYmJiYmIT+wAz9tsGDJfRbPvmEzoGJiYmJiYmJiUnoD9DQP3KkCv0ffUTnwMTExMTExMTEJPQHaOgfN06F/gYN6ByYmJiYmJiYmJiE/sAM/fapUyX0m+vUoXNgYmJiYmJiYmIS+gM09M+apUJ/jRp0DkxMTExMTExMTEJ/gIb+BQtU6K9cmc6BiYmJiYmJiYlJ6A/Q0L9kiQr9b71F58DExMTExMTExCT0B2bod6xeLaHfVLYsnQMTExMTExMTE5PQH6Chf/16FfpLlKBzYGJiYmJiYmJiEvoDNPRv2aJC/4sv0jkwMTExMTExMTEJ/YEZ+p1//imh31i4MJ0DExMTExMTExOT0B+goX/vXhX6Cxb0XHd8xPiKjoryk86BiYmJiYmJiYlJ6Ndz6D90SIX+Rx7xXFcSf5Ah6B3nO3QOTExMTExMTExMQr+eQ//x4yr0587tuW71sOoS+svYy9A5MDExMTExMTExCf06Dv1hZrOEfkP27J7r1gmrI6H/OdtzdA5MTExMTExMTExCv55Dv9OpQn+mTJ7r1jtVT0L/I6ZH6ByYmJiYmJiYmJiEfj2H/rAwQ7ZskvvjoqLcQ3+YCv2ZDZmj46LpHJiYmJiYmJiYmIR+HYd+4wMPSOiPvXTJbd0aYTWC1KcAQeZoM50DExMTExMTExOT0K/n0P/QQ5LtY86edVu3gqOCFvq3XttK58DExMTExMTExCT06zn0P/64ZPtou91t3dL20lron3NpDp0DExMTExMTExOT0K/j0G8qXFiy/Q2DwW3dotaiWugfeGEgnQMTExMTExMTE5PQr+fQ/8ILku2j/vnHbd0nLU9qob/lmZZ0DkxMTExMTExMTEK/nkP/K69Itr++b5/buvlM+bTQH+wMpnNgYmJiYmJiYmIS+n0K/UH/X4k+6HuUT+PQX6aMZPvI0FC3dbMbs2uh/xnrM3QOTExMTExMTExMQn/yod81qSd6+26FfvObb0q2v7Z1q+uK0XHREvezGrNmMmSSnzE3Y+gcmJiYmJiYmJiYhH5voT+pmO551v8uhP5KlST0X12/3nXFi7EXJfTnNuUuaCkoN6zRVjoHJiYmJiYmJiYmoT/50O85jCdloX9tmtaBcuUk9G/r29f1wXnr50nWf+j4Qy8eflFujNgyYi1FURRFURRF3avla+h3HcaT1JCeu3Km31KnjoT+y4sXu674741/Jes/Z32uyekmcmPepXm8I8TExMTExMTExORMvx/DezJW6P/wQwn9l+bNc11x//X9kvVftb3a53wfuTHowiA6ByYmJiYmJiYmJqFft6G/aVMJ/f9Nn+664h+Rf0jWf9Px5rT/psmN1mdb0zkwMTExMTExMTEJ/d5Cv1vQz1Cz91hbtZLQf3HiRNcVN1zdIFm/qrPq+qvr5UaIM4TOgYmJiYmJiYmJSehPPvRnzHn6re3aSeiPGDXKdcXlV5ZL1q97qu7xG8flRhFrEToHJiYmJiYmJiYmoT+Z0J+WbtqG/s6dJfRfGDLEdcX5l+ZL1m92ullkXGQmQ6bsxuyxN2PpHJiYmJiYmJiYmIR+fYb+Hj0k9J/v3991xan/TZXQ/9nZz+R2fnN+ue2IdtA5MDExMTExMTExCf26DP22r7+W0B/+5ZeuK46OGC1Bv1t4N7ldzlFObv8R+QedAxMTExMTExMTk9Cvz9A/aJCE/nNduriuOOjCIAn6fc/3lduNTjeS2wsuL6BzYGJiYmJiYmJiEvr1GfqHD5fQf7ZdO9cVe4X3kqA/LGJYwu0hF4bQOTAxMTExMTExMQn9ugz99rFjJfSfadXKdcXPz30uQX/CxQly+/v/vpfbbc62oXNgYmJiYmJiYmIS+vUZ+idPltB/ukkT1xVbnWklQX/mpZly+5erv2hz9tM5MDExMTExMTExCf36DP0zZkjoP/XBB64rNjzdUIL+osuL5PbRqKNy+3nr83QOTExMTExMTExMQr8+Q/+8eRL6w2rVcl2xVlgtCfprrq6R21fjrsrt+4z3xd2Mo8NhYmJiYmJiYmIS+vUX+h2LF0vod1ap4rpiJWclCfpbrm3R7j5qflTuhsWE0eEwMTExMTExMTEJ/ToM/StXSuh3vP2264qv2V+TlL/r+i7Xu6GRoXQ4TExMTExMTExMQr8OQ/8vv0jot7/2muuKL9lekpR/JOqIdrfB6QZyd+HlhXQ4TExMTExMTExMQr/+Qr9z82YJ/bYSJVxXfNrytKR8c7RZu9sjvEfCtP10OExMTExMTExMTEK/3kL/jh0S+q1Fi7qu+Ij5EUn5Z2POancnXZwkd9uebUuHw8TExMTExMTEJPTrMPTv3i2h3/L0064r5jTmlJR/Ne6qdnft1bVyt3pYdTocJiYmJiYmJiYmoV+Hof/AAQn95gIFEtaKvRkrET+TIVPCI4ejDssjL1pfpMNhYmJiYmJiYmIS+vUX+sOOHZPQb8qXL2Gty7GXJeLnMuVyeySnMScdDhMTExMTExMTk9Cvw9BvNEroN+bMmbDW6ZjTEvEfMz/mSj1sflgelP+iw2FiYmJiYmJiYhL69Rb6HQ4J/YbMmRPWMt4wSr5/xvqMK1XGXkabuZ8Oh4mJiYmJiYmJSejXW+gPCzNmzSq5Py46WlvrUNQhyfev2F5xpT449YE8uPjyYjocJiYmJiYmJiYmoV+Hof/++yX0x165oq21M3Kn5PtyjnKu1BfhX8iDIyJG0OEwMTExMTExMTEJ/foL/Ya8eSX0x4SHa2tturZJ8n1lZ2VXasLFCfJg+7Pt6XCYmJiYmJiYmJiEfh2e6c+fX0J/tNOprbXqyirJ97VP1XaltAdrhtWkw2FiYmJiYmJiYhL69Rf6TYUKSei/YTJpa/10+SfJ941PN3alDkYdlAdfsr1Eh8PExMTExMTExCT06/BM/3PPqdB/7Ji21vT/pku+b322tSv1X+x/2uT9dDhMTExMTExMTExCvw5D/0svSei/vn+/tta4i+Mk33c+19lNy2fKJ48fcR6hw2FiYmJiYmJiYhL6dRb6zaVLS+iP/Osvba0hF4ZIuO9zvo+bVtJeUh7/1fErHQ4TExMTExMTE5PQr7fQX768hP5r27dra311/isJ94MvDHbT6p6qK4//YPuBDoeJiYmJiYmJiUno11noN1WsqEL/b79pa3U510XC/diLY920rue6yuP9rP3ocJiYmJiYmJiYmIR+vZ3pr1pVQv+V1au1tT49+6k6o//fD26avA2Qx1tZWtHhMDExMTExMTExCf06C/2W996T0H/555+1tZqcbiLh/sfLP7ppK66skMermqvS4TAxMTExMTExMQn9ejvT/8EHKvQvWKCtVedUHQn3K6+sdNP2X98vj79oepEOh4mJiYmJiYmJSejXW+hv3FhC/6WZM7W1QpwhEu43XtvopkXERsjjDxgfoMNhYmJiYmJiYmIS+nUW+i0tWkjovzh5srZWeUd5CfehkaGeYG5Tbvmvo2FH6XCYmJiYmJiYmJiEfj2Ffutnn0nojxgzRluruK24JPuDUQc9wRK2EvJfGxwb6HCYmJiYmJiYmJiEfl2d6f/8cxX6hw3T1nrW+qwke8MNgyeoDfefYZ9Bh8PExMTExMTExCT06+pMf/fuEvovDByorZXfnF+S/amYU55gp3Od5L8GWgfS4TAxMTExMTExMQn9ugr9ffpI6A/v3Vtb6wHTA5LsL8Ve8gRHR4yW/2ptaU2Hw8TExMTExMTEJPTrKvQPHKhCf7du2lqZDZkl2cfejPUEl11ZJv9VzVyNDoeJiYmJiYmJiUno11XoHzpUQv+5Dh1klWtx1yTW5zDmSBTcd32f/G8xYzE6HCYmJiYmJiYmJqFfT6HfNnq0hP6zrVvLKudizkmsf9j8cKJgeEy4/G9uY246HCYmJiYmJiYmJqFfV6F/4kQJ/aebNZNVLNEWifWFLIWSMnMZc8kCx8OO0+EwMTExMTExMTEJ/foJ/T/8oEL/hx/KKv9E/aMG8NiKJWW+aHpRXa/XsZEOh4mJiYmJiYmJSegPco3pruWW4BN9/E6GfvvcuRL6T9WuLavsvr5bMn1Ze9mkzCrmKrLAbPts3XWO2bNnt2/fXn5yYGBiYmJiYmJiEvrTJfQnm+DvZuhfuFBCf1i1arLK1mtbJdO/43wnKbOVtZUsMMg2SHedQxJ/pUqV5CcHBiYmJiYmJiYmof/OhX7Ps/53J/QvWyah31mxoqyy9upayfQ1w2omZfaz9pMF2lja6K5ztGrVSkJ/p06dODAwMTExMTExMQn96RL6Ex3Gk7LQvzata1P87D1HihaV272295JM//b+t5NauM/2PrJA+f3l1+qt6tatK6G/RYsWaymKoiiKoijKn/Ip9Lsl+6SG9NytM/2OjRsl9NtLlpRVZl2aJZm+5ZmWSZm/OH6RBV4xvaK7d4TVq1eX0N+xY0feDWNiYmJiYmJicqY/7c/0J5XaM0ro375dQr+tmJqxZ+LFiZLpO57rmJR52HlYFshjyKOvzvHvv/9Wiq/WrVtzYGBiYmJiYmJiEvrvvdC/c6eEfuszz8gqwyOGS6b/MvxLL2ZOQ05Z5oTzhI46x++//66F/kaNGnFgYGJiYmJiYmIS+tM+9LuN4090WP9dnL3HuX+/hH5LwYKySr/z6nu631z4xov5vOl5WWazY7OOOseSJUu00F+zZk0ODExMTExMTExMQn+6nOnPyPP0O//5R0K/+eGHZZUvwr+QQD8qYpQXs7K5siwz1z5XR51j4sSJWugPDg52OBwcGJiYmJiYmJiYhP60D/1p6aZ56D95UkK/6YEHZJW2Z9tKoJ/y3xQvZgtLC1lmsG2wjjrH119/LYlf+y7viRMnODAwMTExMTExMQn991jot1ol9BuzZpVVPjrzkQT6eZfmeTH72vrKMm2tbXXUOT799FOJ+/Xr15eff//9NwcGJiYmJiYmJiah/94K/VKGzJkl99+Mja13qp4E+mVXlnkxp9qnyjK1zLV01Dnee+89ifstW7aUn9u3b+fAwMTExMTExMQk9N9zod+YM6eE/rhr16qFVZNAv/7qei/mWru6am8JUwm9dI6TJ09K1q9Ro0bXrl3lxrp167yb48dHVKzokJ8cGJiYmJiYmJiYhP7ACf2mvHkl9MdGRLzleEsC/Y7IHV7Mg86Dskw+Yz69dI4dO3Zo1+Lt27ev3Fi8eLF3UxJ/UJDhnXccHBiYmJiYmJiYmIT+wAn95gIFJPTHnDpV0l5SAv3f1//2bt5nuE8WO+k8qYvOsXTpUsn6vXr1Gj58uNyYOXOmd7NSJaeE/vLl7RwYmJiYmJiYmJiE/sAJ/Zann5bQH22xPG9Vc/CfuHHCu1nEWEQW2+rYmk47cvBgW/nyJvmZJuakSZMk648ZM0a7MX78eO9mhQrqTH/x4jYODExMTExMTExMQn/ghH7rCy9I6L9x4kRBS0FJ845oh3ezkrmSmuTHPi+ddqQk/vhz7aY0Mfv16ydZ/6effpozZ47cGDJkiHfz9dft8uxPPWXhwMDExMTExMTEJPQHTui3FS8uoT/q0KE8pjyS5iNiI7ybH1s+lsWGWIek04589VUV+t9805wmZps2bSTrb968WRvn07t3b+9msWI2efb77zdxYGBiYmJiYmJiEvoDJ/TbX3tNQv/13buzGbNJmr8Rd8O72cfaRxbrYO2QTjuycGGjxO7XXkubM/116tSRrH/06NENGzbIjU6dOnk3CxQwy7PLv4iIWA4MTExMTExMTExCf4CEfsfbb0vIvbRjq2Rdyf3Jmt/bv5cla1tqp9OOzJVLhf6XXkqD0G80GiXoV6tWzel0/vHHH3K7VatW3s2sWY1a6D90KIoDAxMTExMTExOT0B8god8ZEiIh99SWlZJ185ryJmuucayRJUuaSqbHjjx82Kll7vz5jak3Q0NDJeg3b95cbh84cEBuN2jQwIsZERErT63l/nXrrnJgYGJiYmJiYmIS+gMk9IfVrCkp++SGeRK2n7A8kay537lflnzE+Eh67Mg1axxa6Jfk7XCk1ly+fLkE/Z49e8ptg8Egt999910v5smTN+Spc+dWXyqYNu0/DgxMTExMTExMTEJ/gIT+Ux98ICn7wNqJErZfsL6QrOkMc2Y3ZJeFjWHGNN+R48er79Fmz65y/8GDzlSa33//vQT90aNHq812OkNCQuSuzWZLygwNjZTnffJJi/zs2/c8BwYmJiYmJiYmJqE/QEL/6SZNJGL/sXKo5PhS9lK+mM8Yn5GFtzu2p/mO7NbNKoH7kUfUAJuNGx2pNAcMGCApf8GCBdpd7Uu9x48fT8pcvfqKPG+JEuqNR4sWZzgwMDExMTExMTEJ/QES+s+0bCmhf8PyryTHv+142xezoqmiLLzAviDNd+T776vJc4oVUwNsFiywp9Js27atpPyNGzdqd5s2bSp39+zZk5Q5c+Yled5q1dT3CkJCnBwYmJiYmJiYmJiE/gAJ/WfbtpXQv3xJJ8nx1cOq+2I2tTSVhYfbhqf5jixRwhQfuFX0HzMmtaG/bt26kvIPHz6s3dXm7N+2bVtS5ogREfK8n3xyRn6+8IKVAwMTExMTExMTk9AfIKH/XJcuEvrnL/5EcvwHpz7wxexl7SULd7R0TPMdmTu3GtjTpo0a5NOrlzU1pslkkohftWpVp/PWdwO++OILeWTt2rVJmT16hMvzDhp0If76XEYODExMTExMTExMQn+AhP7wL7+U0D91YSPJ8R+f+dgXc5J9kixcx1wnbXekNl9n7tyGwYPVqPpWrVIV+nfu3CkRv1mzZglC//795ZGFCxcmZbZsqc7xz5p1KU8e9YHD+fOxHBiYmJiYmJiYmIT+QAj95/v1k9A/emFtyfHtzrbzxVzlWCULlzGXSdsdqc3X+eqrph9+UKG/Zk1zaswVK1ZIxO/evXuCMHLkSHlk+vTpSZm1aoXJ865efeWVV9QGHDgQxYGBiYmJiYmJiUnoD4TQf2HwYAn9g34KkRzfPby7L+Y+5z5Z+DHjY2m7I7X5OuvWNa9apdJ/mTKm1JhTp06ViP/dd98lCNoMnmPHjk3KLFdOPe/OnZE1aqj0v2bNVQ4MTExMTExMTExCfyCE/ohRoyT091r4puT4/uf7+2I6whzZjNkyGTKZw8xpuCO1+Trl586dKnw/9ZQxNebAgQMl4s+bNy9BmDt3rjzy7bffJmU++6zagJMnb7Rpc1ZuTJnyHwcGJiYmJiYmJiahPxBC/8WJEyX0d1pUWkL/iIgRPpqFTYVl+R3OHWm4I7X5OidMsJlMYdolulJjtm/fXiL+b7/9liBoF+jt3bt3UqZ2Ld6LF2O17/J+9dV5DgxMTExMTExMTEJ/IIT+/374QUL/J0tekhA/6eIkH823zW/L8gvtC9NwR2rzda5Zo67JpU3jc+xYyk1tvs5Dhw4lCPIGQB7p2LFjomZUVJw8Y7ZsatKeWbPUhP0ff3yGAwMTExMTExMTk9AfCKH/0ty5EvobLy0iIX72pdk+mo3NjWX5kbaRabgjtaB/5IiaYfO559TtrVsdKTMtFktwcHBISEjCfJ1SoaGhEvpbtGiRqOl0RsszPv64WW5v3HhNbgcHOzkwMDExMTExMTEJ/YEQ+i8vXiyhv/bKpyTEL7m8xEezp7WnLN/J2imtdmTCfJ3a3bfeUkN9Fi9OYej/66+/JN83bdrUdasOHTokD9avXz9R88CBKHnG4sVtcvv48Rty+7nnrBwYmJiYmJiYmJiE/kAI/VdWrpTQH7Imv4T4dVfX+WhOsE2Q5euZ66XVjkyYr1O7W6/erfH9KTNXrVol+f6LL75w3Srtcl3Vq1dP1Ny0SZ3dr1xZnd2/ciVWbufIYeTAwMTExMTExMQk9AdC6L/6668S+t9Y/5CE+G3XtvloLrcvl+XLmsqm1Y5MmK9Tu9uunZpIp2/fFIb+adOmSb4fMWKE24aFhITI4zabzdNcuPCyPGPDhqe1u/nyqS8YnDsXw4GBiYmJiYmJiUno133ov7Zli4T+Vzc9KCF+z/U9Ppp7nHtk+fzG/Gm1IxPm69Tu9u+v7rZpY0mZOWjQIAn3c+fOddsw7du9//zzj6c5ceJFecYOHc5pd0uUUG9C/v77OgcGJiYmJiYmJiahX/ehPzI0VEL/87/nlBB/NOqoj6Y9zJ7VmDWTIZM1zJomOzJhvk7t7uTJdrlbp445ZWbHjh0l3G/YsMFtw5o1ayaP796929Ps3/+8POOAAbem6axZU00bumrVFQ4MTExMTExMTExCv+5D//V9+yT0P/FXdgn91mir7+ZTRvXd31BnaJrsSNf5OqV+/lmF/vLlUxj669evL+H+wIEDbhvWrl07eXzLli2eZocO5+QZJ068qN1t21Zdn2vy5IscGJiYmJiYmJiYhH7dh/6oI0ck9Ofbn0USfHhMuO/mm2Z1Ed/FjsVpsiNd5+uU2rFDTebzzDPGFJhWqzU4OLhKlSoOh8Ntw7p37y6hf/Xq1Z5mgwan5RkXLbqs3R08WF2fq3fvcA4MTExMTExMTExCv+5D/42TJyX033c0kyT4yLhI381GlkayyijbqNTvSLf5OqVOnFCP5MqVktC/Z88eSfaNGzf23LABAwbIf/3000+eZnCwesZNm65pd+fMUdfnatbsNAcGJiYmJiYmJiahX/ehP9puP5FF8m1QZkNmv8zu1u6yVldr19TvSLf5OrXKmVPejBhOnnT6a65Zs0aSfdeuiWzYqFGj5L+mTZvmab7yivrm7sGDUdrdzZvVDJ7vvOPkwMDExMTExMTEJPTrPvTHnD17MJcK/Q+aHvTLHGsbK2vVt9RP/Y50m69Tq8KF1Sj/P//0O/RPnz5dkv2wYcM8N2zq1KnyX6NHj/Y0CxRQ3yR2OqO1u//+q67P9eyzVg4MTExMTExMTExCv+5Df+x//+18VIX+AuYCfplL7UtlrddNr6d+R7rN16nV66+r0L98ud1fc/DgwZLsZ8+e7blhCxYskP8aNGiQp5k1q/pSQVRUnHb32rU4uXvffca4OA42TExMTExMTExCv85Df9z161sKqdBfxFrEL3OXc5es9bjx8dTvSLf5OrWqXdsiD06d6nfo//zzzyXZ//LLL54btmLFCvmvnj17upkREbHxXyowuToPP6y26syZGA42TExMTExMTExCv75Dvyy89kUV+kvYSvhl2py2LIYsmQ2ZrU5rKnek23ydWrVurUL/N9/Y/DUbNGggyf7vv//2/GU3btwo/9WhQwc38+RJNZinSJHbZiwtWVJNG7p373UONkxMTExMTExMQr/uQ//S17NJ6H/DVs5f8wnjE7LiTsfOVO5It/k6tfrqK1v8JXItfpnR0dHBwcEhISE2m81zg//66y8J/c2bN3czQ0Mj5bnKlXO4UrVrn5IHV6y4wsGGiYmJiYmJiUno133on1/1fsnuIdZK/prlzeVlxSX2JanZkZ7zdWo1bpwK/fXr+xf6rVarxPpGjRol+sseOXJE/rdevXpu5urVV+S53nvvtmdp3/5swuW6ONgwMTExMTExMQn9+g79P3yQW7J7HUsNf83q5uqyYi9br9TsyETn65RauFCNrnn7bZNfZmhoqMT6zp07J/rLWiwW+d+qVau6mTNnqln5W7Y840oNHaquz/Xll+EcbJiYmJiYmJiYhH7dh/7xrR6W7N7EVNdf81XTq0FqMv2gCqYKc+1zHWGOFOzIROfrlNq8Wb0ZeOEF/0L/zz//LLF+6NChSf2+kvhlAUn/ruaIERHyXD173nZB4vnz1TuBJk1Oc7BhYmJiYmJiYhL6dR/6h3d6TIJ7a0Mjf80JtgmS+3MYc2jR/2nT0wOsA447j/u1IxOdrzN+KI4a9pMnj8GvHTlu3DjJ9DNnzkzq961bt64scOTIEVezR49weS6J/q7U1q3q+lwVKjg42DAxMTExMTExCf0+hf6g+PJ8xPPxOx/6B/QpIJG90/GPU2ZKyh9oHSiJX4v+9xvvb3+2/dGooz5uZ6LzdUo5nWHZsikx/qS8rzuyR48ekunXrVuX1NY2b95cFti1a5er2bLlGXmiWbMuuVIGg5rSp3BhCwcbJiYmJiYmJiahP+Wh398on06h/8vBBSWs9z7ySWpMR5hjrn1uRVNFLfrLvyrOKquvrI69GevdTHS+Tq0KFlSz+uza5fR9RzZp0kQy/b59+5Lazvbt28sCGzdudDVr1QqTJ1q9+oordf26uj5Xtmzq+lwcbJiYmJiYmJiYhP5kQr8W1l0je1JvAO5K6P983JOS0QcdaJcm5nbH9vZn2+cy5dKi/7PWZ0dHjL4YezEpM9H5OrUqVep/7wd8+a2jo6MrV64cHBxst9uT2ryePXtK6F+5cqWrWa6c+v7Azp2RbuCjj6pPIU6diuFgw8TExMTExMQk9HsL/Yme0U9Z6F+bPtVs/COSzj//+b00NBf/svjTPz8tcKyAFv2zG7I/d+S57r93d1vsxx9/lf/OletEokj58gfkf7/6aruPTzp//nwJ9O+//76XZTp37qx909f1wQIFjskTTZ/+m9vCRYockcfHjt28lqIoiqIoiron6y6E/nQ6099kvjrT//2fXdP8nVbszdjVV1ZXdVbVon8Zexk3M6n5OrVq0UJdlHfIEKuP7960a299/vnnXrZt9OjRsszUqVNdzdy51UcKFy+6j0R6/311fa5ly67wDhsTExMTExMTkzP9SYb+pIJ+hgr9dX9WF9ads7V7+jX6yIiR8hTVw6q7PZ7UfJ3/PxRHTezTpYuvoX/ZsmUS6IcMGeJl23744QdZRqJ/ghkVdWvsvifYseM5+a/x4y9ysGFiYmJiYmJiEvq9hX63yoChv9pa9UXeJb/2TL9G33t9rzxFcVtxt8eTmq9Tq1Gj1FuCxo3NPu7ICRMmSKCfMWOGl2376aefZJkBAwYkmE5ntDzL44+bPcHhw9X8/T16hHOwYWJiYmJiYmIS+pMM/V4ie8aZveftjWrk/ZqVvdKv0S/HXpanyGHM4TaZT1LzdWo1b566KG/lyr6G/l69ekmgX7t2rZdtW7VqlSzTo0ePBPPAgSh5luLFbZ7gjz9elv9q1Og0BxsmJiYmJiYmJqE/haE/g8zTX3qHujjX5kV90rXRn7CoQUTGG7eNovEyX6fUhg1qxP/LL5t83JEfffSRBPo9e/Z42bYtW7bIMu3atUswN226Fv/WwukJbt+u/uuttxwcbJiYmJiYmJiYhH6fQn8auOkT+ovtelji+M7Z6Rv6Q5wh8iy/XP3F9UEv83VK7d+vLsr76KNGX3ZkTExMlSpVgoODrVarl23btWuXhH55e5BgLlyoTuc3bHja0zSZ1PW5ChWycLBhYmJiYmJiYhL69R36n96fR+L4gcnpG/o7nusozzImYkzCI2fPxkikzp3bkJRjt4dlzmyQfzabM9lf2el0Sppv2LCh9237559/ZLG6desmbOfEiRdlMzp0OOdpRkXFZcpkyJrV6HBwsGFiYmJiYmJiEvr1HPofOaIupHViVPqG/okXJ8qzfHb2s4RHQkMjvczXqdVjj6mPAvbvTz707969W9J8t27dvG+bzWaTxUJCQhK2s3//8/IUAwacT5TNn9+sbQAHG6aOzBUrVjRv3lx+0p6YmJiYmJiE/lsNdP+J7BLH7d/0TtdG33htozxLRWfFhEfmzr3kZb5OrV55RQ36//VXR7K/suQbSfOjRo1KdvOqVasmS5pMJm3FDh3UvJwTJyZ+zeCyZdWXideutXOwYerIlMQvnVx+0p6YmJiYmJiEflVxN+MyGTJlOhl07sue6dro9mi7hP7HzI8lPNKv33kv83VqFRKiTrTPnWtP9leeNGmSpJyFCxcmu3n169eXJQ8fPqyt2KDBaXmKRYsuJ8rWq6euz/XDDzYONkwdmS1atNA+0ZJ+TntiYmJiYmIS+sOuxl2VLJ7zcNC5zp3TtdHl3UUukxpHdCH2gvZI48anvczXqVWTJuqivCNH2pL9lfv06SMp5/fff09287SToKGhodqKwcHq68KbNl1LlO3USX0O8M03hH5M3Zgmk0nifnBwsPTzoUOH0p6YmJiYmJiE/rCzMWcliD+0O+hs27bp3eil7aXVNEGRO7W7ZcrYvczXqVXXrurqXd27W5P9lT/++GNt0E6ym9exY0dZcuPGjdqKr7yiLgF28GBUouzIker6XG3bWjnYMPVi/vrrr9LDW7RoIbm/atWqx44doz0xMTExMTHv9dBvjjZLEH9yW9CZli3Tu9Gbnm4qzzX70mztbp48Ji/zdWo1dKgK/R9/bPG+bXFxcdp8ndevX09287RreC1fvlxbt0ABNYLI6YxOVNYm9Kxd28LBhqkXc/To0dLDx4wZ07NnT7khd2lPTExMTEzMez30H4k6IkH8+V+DTjdunN6NPujCIHmuXuHq0r/Jztep1cyZ6tOAatXM3rft1KlTEm4+/PBDX7bz22+/lYXnzZunrZs1q5ogKCoqLlF5xw41xVCZMmYONky9mJ9++qn08PXr14eGhsqNGjVqnDx5kvbExMTExMS8p0P/ruu7JIi/uizoVL166d3oSy4vked6/9T7N32br1NqzRoV+kuWNHlqky5OquCoID/l9t69eyXcdOnSxZftHDt2rCz8/fffy8IREbHx7z1MSW2zxRItCzz+uJGDDVMXpjagX0ob6ta1a1fp7RMmTKA9MTED1Rwzxla6tEl+0p6YmIR+b7Xl2hYJ4uUXBIXVrJnejX4o6pA8V1Fr0Zu+zdcptWePU8vcnpokftHkp9xetWqVJJuRI0f6sp3Tp09PWPjkSXXN3SJFkvzOwI0bcZkzG7JkMdjtHGyYOjC1Af1t2rTR7m7btk3u1qxZ02g00p6YmAFpSuKXP2Tyk/bExCT0ez2VfnWNROfKPwQ5K1dO70aPjIvMbMic1Zg1Oi7al/k6pazWMFksWzZjnMfom+K24mrLHWqzJ0+eLMnmp59+8mU7Fy5cKAv3798/4QOHcuW8XQfg8cfVoP+9e50cbJgZ30wY0J/wSIcOHeSRqVOn0p6YmAFpliypQv+jjxppT0xMQr+3WnR5kUTnWuODHG+9dQca/RnrM/J0x28c92W+Tq3y5VNj7s+ejXGjHjY/rM70O9WZ/q+++kpizfbt233ZzrVr18rCX3zxhSy8evUVwd97z9s2v/568rMMcbBhZhAzYUB/wiO//fabPFKnTh2LxUJ7YmIGnpknj0H+SMXPPe2kPTExCf1J1sxLM+W1osGwIHvZsneg0d8Ne1eebuWVlb7M16nViy+aPKfUPBdzLv4lLuhl28tyV7sUkcFg8GU7t27dqo1/kIVnzlSjjFq2PONlm+vXV9fnmjrVxsGGmcFNtwH9bu8EZs2aRXtiYgaYGRrqkL9QOXMatOmtaU9MTEJ/kjXh4gSJzs37B9mKF78Djd4tvJs83fCI4b7M16lVxYpqyfXrr7o6m65t0kJ/HlOeuLi4atWqSaaJjIz0ZTv37NkjCzdt2lQWHjFCTcPfs2e4l23u0kVdn6t/fysHG2YGN90G9Lt9ulWvXr3o6GjaExMzkMwpU+zagH75WayYifbExCT0J1nDIoZJdG7XI8j6/PN3oNGn/TdNnq6xtYW8POXNa/JFa9BAXZR39uxLrs6oiFHiZDVklZ+mUyYJNB988IGP23ns2DFttIMs3KNHuOAS/b1s86hR6o1BmzYWDjbMDG56DuhPKO1C1KtXr6Y9dWdemjHDUa6c/KQ9MT3Ntm1vXcIyd251Jiw01EF7YmIS+hOvvuf7Sm7u1jHIUqjQHWj0bde2qTE5x16X16ayZX2aEKdjRxX6hw694Op8dOYjcR4zPyY/V+1WU/d07tzZx+202WyyfEhIiCzcsuUZwWfNuuRlmxcvVtfnqlXLzMGGmcFNzwH9CbV8+XL5ryZNmsTExNCe+jIl8Uuac5QvT3tieprly6upJn780f7BB+pG375W2hMTk9CfeGnjbb5uFWTOn/8ONPrpmNPydLmO55XXpiZNTvuiDRpkk4U7dTrn6rxie0WcMvYy8vO75d9JmhkxYoTv2/nuu+/KKlevXq1VS80OtHr1FS/b/OefaoafUqVMHGyYGdlMakC/Vk6ns2nTptLtN2zYQHvqyYyLMz30kIR+Z9WqtCemm+lwhOXKZdTGys6YYY+/lKSJ9sTEJPQnXp+d/Uxy8+DGQaa8ee9Mo+c15VXD8R/e1a/feV+0qVNV6P/ww9MJwvW461mNWbMYsjQ500Sozyd8LlFmwYIFvm9ngwYNZBW5Ua6c+grUzp2RXjbYZlPX58qf38jBhpmRzaQG9CfU4sWLZYHmzZvHxcXRnnoxI3fu1GZmsZcuTXtiuplbt6o/YU89pf48GY1hOXIYMmUy7N/vpD0xMQn9iVSz083k78no94OMOXLcmUYv7yiv/oK9tnDevEu+aCtWqBe1N9/831T6+67vE6GYrVjv8N5yo2HvhhJltm7d6vt2tmzZUlY5ceLEs8+q0ZAnT97wssExMTezZDFkzmyw2ZwcbJgZ1vQyoF8ru93epEkT14OF9sz4Zni3blroNz34IO2J6WaOHatOitWufesrZzVqqBE+w4bZaE9MTEJ/IlX3VF35ezKlapAhU6Y70+gtz7RUf8EaDw4NjfRFCw1VF+V95pn/XTRXm2a0yekmky5OkhvVP64uOebff//1fTs7deokq+zZsyd3bjXjwcWLsd63uUAB9fnp7t2EfsyMa3oZ0J9Qq1evlmVat26drtu5cOGlUqVsixdfZh+l1oyLszz1lLxeGuO/pBlz+jTtiem6VqtW1vhx/LdS/vjx6j1AhQqmjPm7L1y4UF58Fi1axH7HJPTfndBf1Sl5P2hupazyFyXuxo070OjDI4ar0P91q3PnYnzRDAZn/CTExgSh07lOIoyIGLHiyoqgk0HB1YK1Afq+b2fv3r3jBzdv0i73m2x7limjTp+sWuXgYMPMmKb3Af0JdePGjQ8//FA6f2hoaPptpyT++DkE7eyjVJra2B5LoULad3kjf/+d9ky9eeTIkaZNm8rPAPjdS5VS561+/vnWrBjHjoVlzWqUf3IjA+4jSfzy4vPpp5/SPzEJ/Xcn9L/peFMC9NK31IU9Yi9fvgONPjdsmTxjtnmVfDcfeECdaI+IuHU+voKjgggbrm7Yc33PfXvvkxeRunXr+rWdQ4YMkbXmzFkm7OOPm5Ntz9q11QxCU6bYOdgwM6aZ7ID+BPPnn3+WJdu3b59O2xkbe/ORR9Sb5IceMrlNFMR+99fUxvaEf/HFmY8/lhuXZs6kPVNvat9or1+/fmxsrK5/d6vVmT27GsR/4sT/PoWuUMGUcLX7jLaP6tSpIy3fsmVL+icmof/uhP5Xba9KgP6lvLqKd8y5c3eg0RfuPiDPeF9oId/NZ59Vof/oUXVR3ribcXlMeUQ4E3PmVMypvL/klReRjh07+rWd48ePj5/wZ5awxYvbkm3Pzz6zuk2FxsGGmaHMZAf0J5jXr1+XN8my8L59+9JjOzdvviYHi2QRz2vqsd/9M/9/bE/kzp0XBg1S6b93b9ozlWZERIR2MUepKVOm6Pp337BBfeHtuedum2Ri2DD1OVuNGuaMto/++OMPrdml/e12O/0Tk9B/F0L/c9bnJEBvez2//EWJdjjuQKPPmnc+6ESWTCczR8ZF+gi+8YY6cShhQlY33TDJBhcwF1DnFG/GPjnnSXkR+Xbot35t54wZM2StL78cK2zlys5k23PgQBX6W7e2cLBhZkzTlwH9CeaCBQtk4a5du6bHdrZufVYOlkqV1Ki8jz46Exj7yDZihKlsWdvIkXdyOxPG9kj6v7xwodw+9f+XIKTPp9icPXu2dP5OnTpVqVJFbmzfvl2/v/uIESrf169/2x+m/fudmTIZcuQwGI0Zax+NGTNGGrxmzZry888//6R/YhL670Lof9z8uGToPa89LX9RbhiNd6DR+/U7H/Tbs/Kkh6IO+Qi+/74K/QsWqNFHy68sl3VrhNXQtJLflZRXkHGzxvm1ndrchZ99NkjYhg1PJ9ueP/ygXlvffdfMwYaZAU0fB/QnmFevXn3vvffkEDh8+HDabmdUVFzevGp0wcaN6nx/rlymK1diA2AfSeJX8+eULXsntzNhbI/6fGbfPrltK16cPp8aM+FjroMHDy5dulTLoDabTae/e5Mmatzpt9/a3CjtS2gzZtgz1D5q3LixNHiXLl3kp7z18m7OmnWpXDm753Uz6fOYhP5UNVBuU27J0EfLFJW/KFFHj96BRm/c+HTQ1CrypEsuL/ER1C4z/t13EbJ6//P9Zd3e4bc+5q7Ys6K8gkxeP9mv7Vy7dq2s1bhxd2E7dDiXbHuuWaMuevLqqyYONswMaPo4oN/VnDVrlqzSq1evtN3OlSuvxF/JTqWNt95yJLxX133oL1RIXiHN5cvfue10GdujPtW8dEnN4ZMz502XayxwHPlrarNXtWvXTrs7aNAguduiRYvIyEg9/u4vvaQGvq5Z4z7DRN++Vu0TgIyzj3bt2iVNXadOnfnz58uNPn36eDcl8cuvID95ncck9KdlA2UxZJEMbS79qvxFuf7333eg0cuUsQf1bCtPOujCIB/Bfv3US9gXX4TL6nVO1ZF1F11epGlVWqiPaMf/Pd6v7dy+fXv8C9Bnwg4YcD7Z9vz7bzVW4bHHjBxsmBnQ9HFAv6t56dIl7brUCXPdpsl2Nmx4Wo6UkSPV+/MpU/6LH1scpvt9dPSouk6HZO4XX7xj2+k6tkd7xJw/fhCmzUafT5kZFxf30UcfuV6nQrK+JH55RNL/Tf1dgfvWRD2eH+9p81znzm24cSMug+yjCRMmqIG43367e/du7VvU3s3nnlN/9IsUsfI6j0noT7MGsoRZ1Hdqjfc5ypdPOKWU3o2eJ48p6EM1a2ez0818BCdNUm/6mzRR43Cetjwt6x6/cVzTKteoLK8gQxxD/NrOffv2xX+dqImwEydeTLY9HQ718popk8Fq5WDDzHCmjwP63cypU6fKWv369Uur7bx8OTZnTnWY2GzRcvf8+dhs2YxZshhOn47R9T6yT5+uXR7LkCNHmMNxZ7bTdWzPrVehChXkkWubN9PnU2b++eef8R/wNnadtMdms2mjzJctW6av3331avVJ2ksvJX4qqlgxNcpuw4arGWQfNWvWLH6a7A1Op1Nr8KNHjyZlnjsXIy8jQerqQf979aDPYxL6U9tAR8OOyp+yh0wPOd95R/052bYtvRv97NkYOZIfqLBUnreMvYyP4JIldu2rgRdiL8iK9xvvj70ZG58qzstrx1u13up8rrNf23nixAlZMTj4PWEXLbrsS3sWLKg+SP3rLwcHG2aGMq9du+bjgH4388KFC9WqVQsODjabzWmynfPnX4q/MND/5gN4//1T8si4cRd1vY8szZur0/wPPCA/nbt23YntvH1sj1ZnPvlEHvlv6lQv5uLFiz/55JMlS5ZwHHmanTt3lpf9pUuXulHaB79VqlTZtm3bHdjOGTPsL71kkp+pNAcNUt80a9o08eklvvhCnSlv2/ZsRthHe/fulRauVauWNmmPtiNWrFiRlLlw4WXZeG3mX3lV4XUek9CfNg2017lXMvRTlqfCqlWTPydXN2zwy7QNHmwqX15++t7ooaGRashvpSPyvA+YHvBxO7dvV6c0iha1br22VVYs5yinaQcPHpTXjtKtStc/Vd+v393hcEjWkdgfFHRy06ZrvrRn2bLqxMmKFYR+zIxlaoNlfRnQ72lqc9cOHjw4TbazZs2w+MtZ/JfwyJIl6o/3a6/Zdb2PjIULq2/xlighP+0//XQHttNzbI9UxLBhbuf+PdeVxC87VH5yHLmZx44dk5Z577335E2ypzZlyhTtei/HtItaped2SuKPP0NvSqVZv74lfiidLdEt3LRJjfApUMAcG3v399H3338vzTtgwID//+h+ktwd6TIXltuKn3xyRja+dm11yuDjj8/wOo/pua784Rs2bNiu28/CEPqTqd+dv0uGftH64qnateXPyZVVq/wyTfGDgkz+fLlt7txL2kCdx8yPyVPvc+7zZTuPHw+LH6FoGntxrKzV9mxbTfvll1/ktaNY72IJbwN8/921TxizZpU3DlG+tGedOuqsw+TJdg42zAxlTps2zccB/Z7mmTNnqlSpIm+A//jjj1Ru57lzMdoI4/Dw/30cHxkZp4bzBRmOH7+h033k3LPHEP/qY4m/PJZt0KA7sJ2eY3ukrixbpmbtrF3bi9mkSRPt65JOp5PjyNUcOHCgtIwcLIlqMTEx2qwy7du3dzjS8crr+/c7s2ZVHapw4dSG/iJFjPEDeJLc2qefVofeH39E3vV9pH1xYt26ddrd3377ze26vG4rFiqk3s8sW3ZZe98SGP3TNmaMqVQp27hx/I1LE1MSv/Qi+Uno96PR1zvWa8NsTjdoIK9Dl5cs8cs0v/GGCv2lSvne6Gq+ziCD/KzorChPvdix2MdNzZFDvcA1c7aQtab8d+uKKtOnT5e9XnhM4ScsT/j7uzds2FDWzZkz1OmM9qU927VTn5Z+/bWNg+1eNjds2NC0aVP5mXG2U2KKjwP6EzVbtWolq8vPVG7n99+rr+3WrJn4STs55HW63+1jxqh5e2rUsMVfHsvSooV3c+bMS+XKOUaPjjh1KqVjkRMb2yMVdeiQPGh98cWkzBMnTgTHlzb9PMd7gnnq1KnKlSvL+9vw8PCkwAsXLmizeY4aNSr9trNDBxVntdy/a1fK35idOKEm48+e3WC1OpPaSO1vVvfu4Xd3Hx04cEBa9d133024IJfRaJReGhISYv3/L8m5rnXixI34aTPMcXE3n3xSNZfriTn99k9JSiovlS7N3+LUm9KXtFmnd+7cSej3o9GX29Wc95K/z3z0kbrG+/z5/oX+115TnbhIEd8bXc3XGWSYN+9Sm7Nt5KmH2Ib4uKnPPKNev4oZ1PWDQyNDXU/eFFhQIIshS8xN/74s2Lp1a1k3d+6NUVFxvrSnNoCyVStLoB5smzZde+EFq+dgJ15oXEsSv3SbBg0aZJDt9GtAf6Lmtm3btMk04uLiUrOdFSq4T9Cp1ZYtasL+Z5+16nS/m+vWVVF7yBD7jz+q9P/2295NSfzal37lX6FClgYNTo8aFbFjR6TR6Ot2Jjq2Ryru2jVDpkzG7NlvxiT+Wrds2TLZlR9++KHb2AmChTZ1zLBhw7ybcixoV+xauXJlemzn8ePOBx80xn/vRX1uPHSoNcXmzz+r77mVLu3t0jGrVjkSDr27uI+0jyK//vprV6R58+byYMKXKFzXmjTpYsK8HdopA202MH33T4fDkCfPnZ72N3BNOUK1yXZTY96LoX+BfYH8bXo37N2zrVurr4jNmOGXaXz5ZfX9tjx5fG90NV9nkCE0NHJ0xGh56laWVj5u6ptvOoKyHs9myJ7ZkPlK7BVNa9Omjez4ZzerS33Zo/0bN9yhg/ou0ZNPrvSxPWfMUFtevbo5UA82SfzyCz75pCUmhheaxE2n01mvXj3tSvJz5szJCNvp14D+RE3J+tqnXv/880+Kt9Nmi86UyXD//cbLl91HEMfG3jpd9+efkXrc78ZHH1Xf392xw7lrl3q5y5/fu6n9svJClzu3KSH9x5/clddL08cfW8aOtW/b5m0ISaJje7TSPgFIuIqi24oDBgxQU5kNGaK9i3Md4XMvB4vLly9rs9MavV59UjO161fI8vv27Uvz7fzqK3Xm6O23TWPHqhshIeYUm337aiehvE0nJ32sQAH17uLAgai7uI+082urVq1yRQYPHqyNtvI0tW//a5flWrRIjfCpUsWp+zPTS5ZoLwTGp54i9Kfe7Natm+cl3gj9ydcPth+kG354+sNzHTpId7w4aZJ/ob9gQa0fO0+e9LHRtQG+587FrLu6TtasYKrg46bWr38qqNgaWeUF6wsJmjYu/7Vjr8njf0X+5dfv3qXLV7JuiRKLfGzPdevUWZPixU0BebBJ0H/0UbOWTnr0COeFJlFTm+Wjdu3a8fO9Vtu7d+9d306/BvQnZU6ePFld4W7y5BRv58iREdJzGjVK/OLWX34ZLv/bvv1Z3e13x+bN6u/044/fOld3333q5e7ff5MyjxyJ0kYmyFuduLib//wTJdmlXbuzpUrZJfS7vgd48EFjyZKm0qVNY8bY3d5ZJjq2Rytn5cpqxoX16xP93SXoy34MDQ3VbriO8LmXg8WPP/4ordGjRw8fzT59+sjyzZo1M5vNabidgj36qOoDixc7Dh5Ug3Ny5DC4fj7nl/nee5b4ebGSGW7atu1ZH69Fk0776PDhw8HBwdWrV7dYbvuQfPHixdpOcTOjo+O0d8t2uxp2Gx4ekzmzHHbGa9fidN0/LU2aGP5/XJfzxAlCf2rMf/75p3LlyiEhISdub0lCf/I1zjZO/gC1ONMi/IsvpC9GjB7tl2nIlu1W6N+82ZdG1+brzJvXJLeNN4yy5uPGx33c1M8/Pxf0wUhZpeHphpoWERGhJbC6p+rK40uvLPXrd+/Wbais/uabs3xsz/37nfGTiBkD8mD79der8ts9/bQlWzb1Z2np0iv31AvNTz9dLl3avnDhZe/myJEjtYET2inVVq1a2Wy2u/u7+zWgPylTXkMFadiwYVxKr/ZasqT6HGzVqiuJ+ocOqSj88MNmL+OPM2Zfsn3zjRpp07DhrdMcxYrJXcevvyZlDh58QX7T1q0TmSdR4t3KlY7+/a21a1ueeOJ/bwAk9992RnDNmkTH9tx6CW3bVp2dmTDB83f/+++/E77Cm9BRCRZ2u117C7Rnzx4fTcn62qTybleNTeV2jhihzs2XKHFrd8tbvvj5KO0pM598UnWhbduS+c7x+vVX489V2e7WPtI+Oendu7cbsn//fq27upl//qnm93vxxf8NSXrtNfXaIn+hdNw/rVZ1pbSgIFPRouoF5PYPPQj9/po//PCDdJ6ePXum0rwXQ/9Q61D5u9PhXIfzffpIX7wwdKgf5tGjCe9c7bNm+dLo2nydZcuqcTixN2PvM94nz37SedKXTR0y5ELQ161k+aEXhv7/SbUj2gXVPz/3uTw+7uI4v373rl3Hx5+vnehjezocYRKIM2UyWCwBeLA1a6a+ayGRZdy4i/GnIU3adCv3yAtNqVLaAFlvl3yXLJVwAtVoNGpDYsaOHXsXf3d/B/QnZSY6wsf37Tx6VGX6fPlMXr4eU6KESjxz5tj11ZfMVaqoGXsmTrx1ui5+ljP7pElJmfLiJr/m6tVXkt3OAwec2mAPeQNwWzz47LOkxvaoMx2jR8v/nuvUydOcM2eO7MGvvvoq4SMp1xE+92ywWLRokTaHqV/mvn37tBFBQ4bMknjtOUOOv9tpt4cVLqxS/rRpt04TdO+uhlO2bGlNgXn4sDoDlSuXMdl5hm7ciMubVz2vwXDjruyjtm3bSjMuX77c05HEL/8l6d/VHDhQvW3u1OlcwiNff60m/+jWLVy//dM+e7ZK/K+8Ym7USL2e3D7hDKHfX1N7T7527VpCv9+N3tfaV+Jyz/CeFwYOlL54fsAA303Htm2G+PP26ltu/fv70ugJ83Vqd4vbisuzr3f4dJJy1qxLQQvKy/Lrrq7TVp85c6b2+eDwCHV93x7hPfz63Tt1mhl/pmGE7+2pnVwJDXUE2MF25UpsrlwmeT9jMqk/DNqXrV96ySaP3wsvNNHRt/4uFixo9mK6Balt27ZVji/tu2h35XfXBvR36NAh9abnCB/fTW1Krk8/9XYZIG38T+3aFh31JafVasyVS32SGZ9LVCLv2lW93HXrlqjpcKgvNsihFBkZ58t2ShDMl0+9pOzY4Ux4Z6mNmUzq4uhXVq+W/w2rUcPT7N69u+zBhQsXur1B/T/2rgOuiayJBxB7OXs/e69nryAgil1RDzvq2fXu1LOdZ0U99SzYxdNTsfeGvfeKHQUhm2STbMROlSb4zXsTls2mbSL6eWX1l19Idievv5l5//nPv1yxwIDRUxZT0JiUiZGCrq4e+fKdLF6c+cRyBgSoKU1nhpp+/DjBi5Yuzdghc9s2Yls2aaKU0p7o0BHGwn6xPnr69Kmbm5unp6dJrwTs3dDCmEiOf6R5c63IbL50iTAB1Kih/vuOT1XnzmTdmDZNf3I4YMB/Sr/dMnEj7tq1q7m4qP+UfkvXL+wvoC7PejtLn/Zl8mQblH4amKIoV46M5oEDpTQ6z9eJf/aI7AG/vkqzSkpRCf7kbj64n0vRx/T8+OOP0PfwujVmK3zeO7K3TXUfPpx4gLy9p0lvz0aNFJQ8WPMPm2zbtpFgKVhteRsANH74BLT/f8NCAxsMxlnCa3BwojmZxpAJf39/RMVYDRD8THVHQP+ff/756TKNET7SZVasSHyW585ZSnKn0aRQbK782TPu7zKWtIcPkyWucuUMNX3VKrJnd+pkUubq1eSUzNv7ufRy9uhBkNnTprFSsD1wJYeGkvW2fHmRTI1Gg57pkJAQk8P136lYgK6PhnpKSoodMocOJW3YsqVnrlyXRQl0bS1nrVoKUSItjtMVKmQA0ZEuc8IEMuNGjGCltOf+/WR9a9pU++X7KDAwEBoQzFGTchCkMW/ePF5mTEwq5vqANxljPjktTx7SemBU/x3HJxcRQaI3HBy44GAM51U0aPCf0m+3zDlz5sCwWbJkyafL/Dcq/SPZkaAuL3q3KMrfn5wajx0rXSbuf0qan0vZqpWURuf5OvHPaW/IOcM4dpyUop58JIebs9wryEsbNWoU9P3WrVsxTW9LbUub6t6/fxDlXhwnvT27diWhritXqv9hk83LS5xINSwsGdfZ5cuj/vELDYkRl8kJPZRMPmWK6SBmY9cpXGq1GknuZ1o8Ivt8dUdA/+3btz9dpjHCR6JAdFiWKKGymvjTzY1gEvz9NX+XscT+8gtRwQXZbbUnTpC43mrVTMps04bMo8DAGOnl/PNPYl03aqSQgu0h3ZSUJHdygv9pycnG3q8+ffqYO5j6dyoW6BjasWOHHTLv3+fy5Qtv1oxwgTdv3rFYsfCwMDvZkHbt0tLwbkYEDf3+ewOTT7pMT0+yEwUEaKS0Z3x8Wo4cBJiq0334wn00evRoaL3du01n47lw4QJ8O4C6vfH+w4fjKLuR2D7p3DmDz+dvNz7VK1cSRb9xY7KPhISQBSR3bt3XyqzFPXjA/vabskEDtSHn71dSTpVKhfQtd+7c+U/pt6fRfVUk19WaaPi3Bsbiy5EjpctkZ8zAEDcyiMuVk9LoPF+n3sEcSwhDO6k6SSnqFu4g3Oy8vQUvDckTnz9/HpEcAV+VY8vZVHdv7/OU03qo9PYcNYr4V379lf0nKb6RkR9Ai8ialXnzxkBr27ePrL/Ozszhw9p/jBJgLPPt29Rs2RhogX37yHFHpUqshSNFEQ0iXMHBwW3atIGvLl++/IXrzgP64U2myBQhfCQKHDpUJUTcWrj++iuG7ujKv8tYUjRqRBD8Am5WLjycYBqzZ9dpxd7ZqKhUmCwwkETzyHI5w8M5Z2eixoeEcFaxPXix5csT1s6wMKHMlStXipJTiszUf6HSj+A3Ly+v2NhYO2SiYu3peQ0neNWq0/r3V9lXThjzJhM7rlunpu4Gpa0ywX6wCjQVyuzalSjNa9ZEf8k+ioqKQooVuVxuUg7LsvCtm5sbf1JK6Dpk8tmz34pEIXP/3/TkWQktIJOpFyzAP5miRUks782bX0s5GUZ76BCoc6pOnZiSJXl+MWXDhl9he+7bt0+Uy/k/pd+2Ru+p6gndGxgTGPPXX9DNLyxGO4ln7MiRZChPmULyxTg76zTWWQh4vk78MzgxGH69mqKalKLOfuNHRuLkoRgs+Pr1a6TuIdpP2nv4KiuTNe1jmvS6e3iQLaFLl17S23PuXLUo9OofoPhi5G6XLs9NHSITpsWiRZmHD7l/gBJgUubatdE0/YIuNRW2UrI3P3pkIvujMbaHvzCAsnPnzhaSfX6OuvOA/sySKUL4SJEGqi8MD2i027cTrVY8OhrsK7mjo/zePe7rH0tcRARD9XERvx7u2dytWyKZO3YQo9HNjbO1nK1aKemRmhqxPbDvmsP26OW0bQu3xR05IpQ5bNgw48g24aD9Fyr906dPh+ovWLDADpnQHdAp+fLJ79/nbty44elJ9P7SpdceOmQzFOfECS0ytAoPCvCCTxDNgl9JFKjRpGAwnfT2xGg6Idv9F+ijY8eOQaONHTvWgijQ3uCe06dP4yNVqrCY0EMkKjw8mVLnESbcv9f45EJCGNrH3JMnehugVSviShAQzH/pcqamJj15ErNx48vhwzV16zKYHTr9PwMjlXKUKerWzcT2vHbtWs+ePeH1E2WOGTMG8R1ftdIvE1xSPv+SSn8HZQcku4zdtg26ObJPH+kyld7eROlfvpwpVozsggKMgcnHhXydeMWmxsKvZ5Nn0+qseyy8n3uTIdllCcsSYN/169eh78eN04NzCioLwrcvPryQXvf69UOoH6iD9PbcuFFDfT/Kf5Lii3wje/eacIalpKS5unIUD6rUaP72SoBJmU2akC15+3ZS/WHDCKf1jBlvxAu3KWyP8Pr555/h20mTJn3JuvOA/sySKUL4SJG2Zw8ZPBUrshL7qFMnAzzD1zyWNFu3EndX/frida95c7Jn79ghkunjE0l506NsLefvvxNFp0MHJWJ72OHDLZft1Y8/8vTKejuEYfDMhzHM+is8nvq3Kf1Pnz5t3bq1u7v7w4cPbZUJij7lV5SvWKH3zR88eLBVKzdXV/eaNQ+zrG3lREL9UaNMh7DD0spT+kgUePAgOYN1dbXhxOztWz1WHt58sT6C9RCxVRZEoV26iiYIUquJMZM3rwL2HWNp5cqxGHP19xqfahotqfTwyPCW0pxIrIBu8suUMz4oSF2tmrZlSwUObl7Lz5JFUbOmasAAtb+/9uJFstvdv08+z5tXZ3isbT9kiOO6dOmCycKtlnNt9Npm2mbwaiwTcz54enqaOzv6KpR+Y0Xf+P3/Uel3U7pBt5+IPxG3bx908/Pu3aXLVLRoQTa/nTsVjRuTNzQG30KjC/k6+asYUwwKcEN7w2pRy7Mk7a6s0ombNxM+pkcIrV2rHxm11bXh23uJ96TXvWxZxtUVhpBbqlUwcrpM9NnUqKH4xyi+YWHJ1KFlmm8EwT/oyh058vMqarCtDhgw4NChQ1+yPdGBlCePAjO/nD5tQBPByzSH7eEv0JKRfg5q8cX6nQf0Z6JMIcJHirTevVXC0Hyr1+bNxEioVo35SjbskydPDh8+nHc0CmWylBGfNfJTqnx9ibPDz08oMylJn1FIqUyxtZzBwXr6xdDiZchCGhRkBTWxYgWBYo4Ywcs8evQo9BpUxHiv5Y3Vf5vSv2TJEp4e3laZ6cAeA6162TICoGrRov3o0beky4QVxtFRnjUrOTEwWU4wgGlWO5V0mVOnEj6Mn35ibWrP1q05DKjbHLO5obZhYEzgZ+2j2NhYNLrCBZnsjK8DBw5Aq/78888f0+F/Js+c4cIsY/Pmvf17jU+9diQg+UWIv6pjxy9ZzoTr1xW5c/OKvqpMmciePd8tXpxw5YrOiFhp61ZNxSzn/pK14i5fzpT2XLNmDaaxB3XrCvyiRZmg8UMRm2ubG8sE45BnJf7bwHvMKfoStflMV/obKxpD+156fymenizrOna0QenHNBPnziGsX714seVGF/F14tVC0QIKsE2zzXI5n3HPHOQOjqHZZE7PDh4kZF7Tpk2D7j979izKaa9rD3KOxB2RXvc8eZjmzTuAkKioKInt+fAhWTcLFGD+MUr/tGlvzOUS4q/Dh7WYsWv9ek2mlxP0ElBZ8MyOD+r6Yu2J1R88+AV/slGgAFHdRDkKLGB7+Ovy5ctwT9u2bVmW/QL9LgT0Z+JYEiJ8rIpiWR36jEJDkyX2EctySFJ57pz2a9iwkUR8BFWgRTLxjFuzb59ICKj7ZNf09RXKxNx2deqo7StnzZpk1G2UuTAlS+qseeXjaTAx5+7Oy/z999/RXWrOkwqv/yqlX6FQYLQfahg2yRQCe0QW1JAhE0Fm48Y+J0+GSxQ4dChRVfv2NctUe/EicSQVLsxwnIlyxuzYoalXL8YwENnTk6NRrbYFxK9ZQ3CMXbs+B40f9spG2kaftY+QN2n06NGWReGCA50FCw7oBlDCVatMb8fIQeTqyv2NxicXHCx3cJDnyMFFZCQj4jDJd/nyX6ycUatXMzSPKvvttzGBgR8iIy3LrFSJLNHZZSEbh+789PZEbmtQ90FZN/ZNGD9bV1MXxud3mu9En8MExINoGFr47PHj2lGjWHj9Jyv9RzP7qhBSgaS1Orvswpw5MCYefved9Gef5ckDj5zYvv1mv37w5lbPnpbv79XrJo3FuSn8sGNwRyjAkGtDLD+78PxCuC3f+er0nPQafNKpUyfo/i1btuANXsFeJMvYtVESC3/o0DHKc+yD+DCJTwUFHc2SJQIePHDg+NF/xFW0aChUZ/7885ZvGzbsOtyWI0d4QMDpzPrp/fv3z549G0/94GrdujW8duzY8YvVHXqzSBFS/QULMqrfuvVd+KR//xuC24JwsP3555+WBaLp4uPjc/jw4c9deAzc7NOnT2a3idTKwjVt2kVoqwoVntj0E+3b34Gnune/9TWMf1QNu3XrJvr8xLZtsFuHZ8t27NAh0VcXKNP2ozp1hB+2a0cq1afPTfuKAQ8S1VA2+3bXrlZvPrVhAxQgtFAh/hNvb29zXYasiNCn0LNfoD1hWHbv3h1e/7/d6ufnB7Xu16+frQ9u2XIyV65n0Bfjx182/vbgwYPu7n1oHvcRR44ESZHm7Bzh4BDx55+nrS7C/v7njL8KqVAB+hpehR/mzv2MkkSdtLVqoH9mzRpe5nE52CvzPssbdPQzDokffvgBGmru3LlW78QFZ/PmwHz5nlGkk+m22r37uKNjRJYs8n37/jab7/VBg6D77rVsKfwQlhQ5qBEODscPHPjcBYCfuOvujt79O7C2SNuYypV7wsN/YLn+FG1n37592L+TJ08+cOAArrdLly618Eju8Nw4PkWfBwQE4FLGf9K9+226ldz+Yh1qg9JvjN3/Sjz9FRii9Icmh76/dIm47Vu2lCiTY1kSv5sli47j9NzV6fm0zVlaIr5OvOap50EB+qn6WS4n3lbvVD/EEkRHR0P3t2vXjucU93tLwnynvpkqse737xNnSePGg5HZWnp7limjoJFG3D/A03/1KgFclSqlshg3qJfZpQs58q5cWSGXf2rdVSrVvHnz2rZti+o+mO8bNmyIiIjo2rUr/CmK9fl87XnhwnuaLseg+kePEpftd99peJlWsT28zPj4+N69e8PN69ev/9z9LgT0Z+5Y4hE+VkV17qwH6NvUR0eOENdm8eKMxeb8EvMoLCwMT5zhEh33adauNWYi1i99t24RR13RorxMGD8lSpCmuH8/0b5ynjpJUE/FZFc1QUHW6/7hA/HbOTikUdamx48f42KoMRV2wyN8hLmW8Tp//n3lyiy8fnp7wjoM0xazg8E1cODA/+Nap9Vqe/bsKQxrli7TJLBHeN248ahFC6LEDBu2VAKonRAhdOxoJSHdwIEE4fPLL6xxRysKFCDjsEQJ/jO5PBnJFeyMX8r2xDkiG2p0lxMuf6Y+ev/+fZs2bWBaPX361Kq0X3/9FdpzzZqDUKZvv1VZEIusyoGBXyKr9wXthRJMCXj9FJmKGjVE9F/6k6iqVYm6dfy4OZnnz58fOnQovH7KPEpWKDR165KQ3Fy5Ynftklh36DECSHOOmCQbmtUhFDf9s2ftpP3FNQHqgqvTli1b0C/GL1bio+AUFkamg9wBXjUpBlDwmTNnwrPLly/nhUPBTOZN+g/eY+kqzhSHxlWnqBPpTqZp1Eiq0h8czO98SDqhqFPHcqOL+Drx2q3dDQVoomxiBTqs6g239Tq2CBN/3rlzB7p/zJgxvJyNMRvhhgEvBkisOwxiypVG4i9vWCTIE9W9SRMlDXvV/AOU/pEjydEz7ExSZIKuj3MMtH/7yinSDDCxGmzMvDKNKIWlS5d+mfYcNOiFMR49MVEPzmYYPQ+6FGwPLxM0MEzTC28kllOtVh88eLBv374nTpyQ3p5CQH/mjiUe4WPZyImI4GjCGXlwsM1Bot9+q7A8ib7MPEIvOOxA8CraX1W9e2MGTZNKJckxJpNxFKwMN9+8SYznMmVUdpcTllDQ+EEIaP9S6s5SaGXSo0dw886dOy3kP+IHsDDXMl6g8dMdnf2U9oyNjd2zZw/aughvw1M7EZPVl1zrECYOReIHsESBCEA1BvaIrvnzz7m4eMBPbN9uyfMXFZWKK8nJk1aQbFu3kp2xbl2FSRwXkqskBgfjhzt3xlolkzDXniQrdsOdsFEWURSB19GvRn+mPoLZBO3z008/SZG2adMmeizjZxVoOmvWW7hn0KDPntU7jAvLx5BMoAWZghqdnUnZtNSRCuNJx4qjL5TduhFEdHp6KVOosKE4oWBew6ZpR8JEGDxoMbKVKiWZ34yMZa5fT0Zj86ZyuaNjUJZalSnUJ2tW+axZrGXnoLFM7Nn27ds/oisVGuSw08GHGzZsMFn3/XH7SbMrCC/L4bjDQjMS15b76cnRb93iaNg3o1Zz/yn9NgyOfHIyst+kvkl68ICMwjp1JMoEI5Uo+rVrEwPg0SP94LbY6CK+TrzucnehAIWYQpbLWVtB4nQXnD1DaS70+9yKFSsyEITxp+AGD87jo1TWES3l15smMUM7/6C3t55f7++u9CcnpxUsKGaotCzzyhUud26yBMyZo7apnCLNwMvLa968ecbJNc6ePQvf9urV6wu0Z3y8PstjeLgYj96nT0bWequ8PcblXL9+Peoc8fHxFsoJVsG2bdsmTJiAiVThatOmjYhyUSKgP3PHEs/hY7nKK1eq6VmZwo4+GjuWpeE9qv+v0t+vXz80Mo1R70ypUsQVd/q0STkI99dSIw1u/vVXDKx8ZXc52WHD+spmo7tXSt2fd+pEWDv374ebESm72cibyF94VCXMtQxXaGiyk5OcbueMKGeTxMaE+evv7w9zGUcvDHiY43FxceiQCwgI+H+tdQgsgcllk0yOS/nmG4WQscfC5em5hVbaw4JtP3/+O5Dm4WEdg65Q6NB+fvHCoCMi+/Ylw4ymv3w9ZQp+OH48OT2YOJG1oz0jIpJlI3+BjfJ7nQ+8FlUW/fDxw+foIxwD+4ziYUxeV69epQduvaFeu3ZZyqiAXCDlyzOfdSwpdIpGikYkEyiTBV5HsiPtk8mOG0cQEIJ8eRmOnt9+I1/98IM5mbg0YYII4eSSVG2OYydNItTIMtnzzp1TrYUsip4eMECFyYjwOCLiwHE8iYL/bdronj//ILE9r1+/jpDdw4cPC+UfP34cPuzQoUMEjXMQPTj1zVT4qabapvA6480M/nN8asSIEbwcJD3r1En11QXyfuXsPc5yZ2jcxLREfXb3qlUlytQEBpJjx9at9btgrlwkDjgszFyjG/N16pdaHZeTyUkgRrpQc4VUc+ps8mwOcodLwSRzR716mtmzZ8MIOHHiRIZ7MukJCKnCVpFY97VriTnbrt1CkLN3717p7TlmDJkSkyezf3elH3Mf1q6ttkkmugHMZewyfhbscli/eCSP5cULNGzkwLn5+ROXbNsWay41/YEDcVSdJV9JxPYIy5mSkoKk6QsXLhRJhq/u3bu3ZMmS/v37txJcffr06dGjB74Hc0iVnrfTXE2FDP2fYywhwsfy4YaHh5KGQ6jt6COwHtFJo1R+ljGvOXyYKVtWY7jZiGQyDAN17Nq1a3h4OOrE/FfJcjnxsObPrzPT6SqqcyMjB9xfrRqxf4xxMlLHJ83JtVHmAkJq1pRkRL0eP56wdi5YwE8ZGFfmxZtA+PTsGUnjMVjjsz5rGoVB5D1cYLgKnZEImmrfvj1M8y+/1qGPGdqEFbhXpUjr2FEn3YN+7x5XvfrvFFXV5cWLF8bSEhLSihYlE+TMGUmJ83A2bd6cgX1NjYtTwK7q4BCzYwf6a/FzFxeOUgzbCXHJs7cVwcFeC6zMVoY3Z9+fzfQ+SkxMBFPQzc3t5cuXUqRpNBrUbrNmfSjyCRrBnT6iYXb79ufKG8NyrLvSHVqmBFPiL81fzgxRkNZr1tshE5YgEathRpUpQ7qyeXOTMjEHUbt27aKioqQ4ywymZ1iY0tOTaOiOjm/nzv0owTkvklC2LPHrHTumVfbqRRzBc+bAh4GBmoIFGUyVcORInFWZCoWiV69euJ0ZFxLzZC+g2cpED7bVtYUG/+U1MU076jJ4ZX766Sd4ZOfOnaIps2yZ+qtT+j9+xTz9oEyjOUvUEaWSmJ5ly0qUqV60iNzfu7eB6+vkSXONbpKvE2XWUtSCYgRpgsyV84L2AtxQga2g1RIe32LFlGgHw9bMy4lOjYZ7cilySaz7vHlkn/7++7Ug56+//pLenvPmkW0SrOG/u9KPuz76s22SOXIkS3OSMqdOWYqaByXgyJEjaOsbawbmSoUReCtWrPjc7dmmDdnj166NNuVHT8uVS+HgIFerUyRie0TlBIUD7RxM0wtqQVBQ0LRp0zCMCS9Y0ydOnLht27aQkBDUpTZs2IDN1bdvXzR7TJyZUDaPlTQtAA/oz/SxhAgfC6ZOSIg+qdCTJ3ZiPevUIZv3n39+lhMzpgzhvoRN14LMjRs3Qh3BAIMxicEkoHzoF5OAALK4dTKbKZwdO5boYePGwftnz5Ipo5dpcnEp4xPhkaElyubKRbbVu3etw6WiacjBi8GDb9y4gT1ludNFCJ/79xNheMMUPn48HpnRo6JSrZYT1lsYongKhEgef39/MFCNizd+/HiKftn+5dc6/OmVK1faJBOBPfnzKywDe4TX6tXvatceBb81aNAQUHNFAgMCCFVO/foaiXVHtyWsyRkzneqF2ubNP6amKosUQTRXaurH3LnJxCH5m21vz9SPqdlC85AguvGPpr+ZDm+Gvhya6X2EPGYjR46ULrNPnxHwSKNGR6z2VPfuz+m2pf4cY0mr03ZWdkbowVXuKtmP1CRWMDeT+wp3xSaZibdv6/HPWhPeMe7ePb1bwZRM9GpPnTpVCIuFDZTfO8DkFsJiM/AX58+jpSH/5pv4kyftmEd37qA7Rq7R6NR//EEsE29v/OrBAw43Tcrf/RJJrs1dSK44YMAAtdpET8HuBjYhbHb37t0TPVhIWQijTeC1uLK4Hiil1aLNo0hnF+UPxx494r5GpT8z5Waq0h/GhZEoaUVeYkPDmg4dXLy4RJnsxIlk2/v5Zz1GrV07YhSuW2eu0adOfY1nncYyuym7QTH81f7myrlKswpu8H7uDdsq5TwOwQQNHz4YeAXyKMhy9i71nZS6jx9PFtmhQ7fDYIKtS3p7ItF469bKT19oYDUAnenaNe7oUc3WrZqVK9WTJrFVqyrWr1dblfno0aM+ffrAq32K77NnHGz50JhgR9k6ltRqrnBhop2ULMmYKyfoT2iao3f/wYMHEsuJRG9g1GWKEnDmzJlevXrBq5G3MgXqni2b2VQ1PXpEUj6NdxKxPcblpNl8iGIEC5/QqT9o0KDFixefPXvW3GqIkEdYEEHBSjPy04DGDxPth5YthYD+TFeqrCJ85s9X0+mstLuP/PzUNBGyMtOVP+2xY2Q3oL4uCzzTvr6+UME7d+7A+zlz5ghzLET27ElWM/OWnp66gFoFBCdN6J5e2L0m8zm52rcnvivQ/6yKek9Z/7QtW2I896xZsyx3ugjhg17t8eOJgx/WZMrf9c5COc+fPw/ziAcbYOS90OciujDmytvbOzk5+Usq/adPn4bfha0hLP3MWYpMHtizZUuM9HJCQzZvHt6oEQkImTFjhnCqwr6ERyh79sRKrDsClPPlyzAddV5e0MXRNBHNSzpC3syYERKShNwD9rXn/cT7RGe7ULpYMeXjBHI2XkBRIDktk/sIZ9POnTuly+zRYzE98FxhtdPXrYvGTHafYyz1U/UjGhGT97Q2A9fXRdkFPqysqCzn5NJlvkK/wLBhZk3ob74hcUEUoS56FoEMhw4dEn1ukgCDT1OlWbuWyZmTgK5r1uRu3bJvHi1dStQbLy/SvNozZ4hlUq6ccMwvXfoO9k24p3p19YMHpoHBJ06cwL3v7t275qqPdQRLxsBZRqN4CysLp31My6cgyPPnH0jSBqgm3Dxz5kzjMJhP7Pd/ndJ/n7vPm1Opb96Q4VKggESZ+gw16Wc37IgR5M/0pAnGz7ZsSTD0Li5aY5kT2YkkqEhlltB3JDsSbvB76wf3FymizJfvOLK9ikRVZavCbSFJIVLqjjC1SZOOgCgYf9Lb8/RpreXsQsbP7t0bW7u2euDAF336RHp56Ro21MCWkD+/AjUT4//GmEWRwLi4OGS6BAXRPqUf57a7O2ffWDp1SouA4AMHxEFOYIlt27YN9QPY9S9evGib11Oj6dCBJE/g14tPUQLwhBEWR9HnCxcSRQ00e3Oidu2KpcP1okRsj8ly8sey7du3nz59elBQ0MuXL632Ea7s/PHImzcZccZpCQmKPHmeODl5tGolBPR/DqXKMsKncWMFZdTW2N1HDx9yMIScneXm6D3s7ndFw4a484koxYQyWZZF9jd0HKBr7bfffkOLR1mwIFGpr18314ZajLCsVg3eI6PI/v1xdq7JFNuDObmWLVPTQCOlVVEpajXx0RQrhgflBw4csIrJ4XMt37hBDl1z51YglAIT0oEWmJho+hQOnkVKUOPIewslxEjEI0eOmKv7nj2a8uUVO3dqMqXfHzx4ADqBm5sbehlskokmELzaOo+ePEnKl+9aixbk+G7Tpk28wN27YzFNNWZ9lCgQaRIuXiST+kNkpNzJicmaNZVO//enT5PttUaNTZti8EDAvvm+ImoFOQ9f3R0NkprqmvDn8fjjmbiGgJmH55l4m0SB9eodpI7hH612ulKZwruiM1fpH6UaBa2RXZ79kNYgQSTo+qDxw1eg/UuVmZqqLF5cyM9jfCmbNSOzfvt24xNy5Lg0mUXb5IEbDPgTlDadrHiw2VHQpH3zqGtXJc2ARqBxHCwy2bMT2Hb6Go33g64PGj/cBto/2AAixxQsrRjns3HjLqFDc9Qotn59xeLFetDd06dP8TahQxCjeL10XvDejSN5Y4/GH+U9UOfPnxfpbxgB9Z/Sb4MScI27Bs1aka2ICEKkdpIoE137mvV6rBvmmlb17Wuu0du101Eo/GtjmevU66AYbZVtzZWzpaIln3irTh11qVKErnXx4sUiUa251nDbyfiTUureqROB5i9efNnY3LRc98ePOXp6Jpe+0FSrxppU7h0dCVNE2bLMd98pYKf39lb26qWks0wcKCxCTOJOjxARoeZnst+1O3cqKlbU7jTIstG8uZKmd4mxeyxNnMhicmLh6WVYWBhG0SGiPSYmxo7xiUFga9as+UTlD7RnPkZWFEtUowZZsyxgE2NjU7NnZypVmicR22OynDdv3vT19b18+XJKSoqtcxNUK8Rqg3V37do1fam2b4fBcahgQXJ6PnToZ4WKWUD4BAdzNOGMPCKC+5Q+gjHPRwVYLScYPwcPHhw2bBifj8+kTFiRoIkCvPNUCSu3tj3hteTOnjWWuXXrVmHQxYsXL9A2Axsg8e5dotCXLm1Jhw4Pl1OI28P7GpjFMFTi4lLtm0eI7cGcXCEhHGZvheFn9SyGyZEj1NHR09MTNN1nz55JgKPomVjB1KdEqxnGZL16xAUQEBBtspyYTRN0C+Gma7XfL1y4gF4JdIGLHrx4UUuzvMhpXAEDi8n161r7xhKq+2ADt6KWMChAxid7UoA9GM1s6zyaOfNNgQKHXV1J7iHewYHtuW5dtE1zE7QiGqFLtsioZctIFGaXLvreTklBJpaRfUmWmIUL39k333tG9oQmLzluIY0eUc99O5envMusNeT69etI0ShdJgz7rFkf4hgTnd6bvMqXJ57moCBNJir9U9UkftSZcTaZJ/QKdyU3Q8jj56jnSJGGB3HG8EKD7emHH4ghR/nBjBdeY3eeqD0xtIbXBDxcXZdUqBAxd+4nGs94hn/lin5hVzRqRNS8HTtEMt+/Txs16lX6/GUHD36Z7tBUNGtGwtWqVfvVpM4Der9oRYIlnT8lwyje394Q5wvC+v3e+uGxYR/DeOhSpUg5jdNy/af0W7nOaM9As9ZR18EjSdInTk4SZSrq1yeGbLoupaHBRsoWLcw1Ou40p0+b4IQ+pz1HIPtMBXPlLMAUQF5RuB8GVtWqv6IaJ/JHaO0AAIAASURBVBI18MVAuG1D9AYpdUetd+vWhzjsbGpPytcnPyo/W5IpeVZ71vKAw1SdWbMyfn5vt22LPX48/ubNhIiI5DdvUk2B/Uzng8zw8KWkTJ48Gb3XSNrI+9LM9Tto/MScq1iR/+TuXQ41lejoVLvHklKpK12a4ZU20LAXLVrk7u6O89MYqyd9fB47dgypvs2NpT8eb896sjq8WpaJFE/I2N21a1f+GPTUKUyBqbQMwu7cWde0qbdEbM/niD14+vQpj+P09/cHY4+jaVYWNW5M0q/SxPWfT+mHhdgY2qRev56pVm1qj1PQgJ07Kz+x7qtWEd0I9gmT5YT6Pnr0aPfu3bNmzeLdWkJ9woRMllVQSGvle4SRsMoNynHu6WlcziFDhoi4ejG0OiQk5B1Fsprk3DAIGyhalPTF1Ae8k9i+fuexPfhno0bE3btvn/VzA3WtWkfy5xfOFMsXKhOdO/eUySJAxxWC+C14pvlsmnwWTIljCcYPAtVA+xfJ3L1bmzcvWTqKFGEKFWKECsG8eazlUE7hJVL3J0+eOWFCcIMGyt9+Yx884KSUUwjssW8eJSWlVa3Kliq1FnXWiIgIqycn5q59+zSImiAovgYNoEViBQwTLwYOhE/qlbqFIeP2zffiSsLQvebkfUdHxsmJOc+EkpSXinyJaYmZtYYsWLAA811KrzuSarRqRU5lwXy12u+DBqkseHntWOsCogOgHRzljgGaAHOi1mvWo1VwNeGqVYEvqUKPMT/mLvWSJTxiXvjs5s2bqSNySZUq7Nmz1nNoHK1Rw4fuCJhkEBZMdNPYsSafO6fPoJKxOg0fTioycaLJ9jxyJC5nTkao01euPJvGZvg4Oz8ROTRhv6DWtZxXe0BnwCNEnj4Ro3gPxB2A9ztid8D7rs+7Ilpsy5YtQpcBn8T6P6XfNiXgsPYwNGszbTN8RE4RGx/Nm9oGquS33wpPwLnr14XuMeNnYUeBfgoLSzaWqdQpYb5lYbKoObU5DNI38m/SJ/yLhg3JXhIaGioSNe3NNLhz1ttZUupetaqCrp4sckTa1J4Y3l7oWVFyGshkD9IGmffKp2HFFy9+J72PjBPE8PsoIuFAhdVoNOfOnYP3P/zwgyWZT5/iCZ08SxYuOBg/mzYNg5gjP3EsIZNP/vzMoUNnUC0D/WDt2rXGYW02jU+1Wo0eetjUjY4+SYScQ1B1XGQ8tK2PxB1J/ZhqUiYCDHbs2IFcOnMoC4GOMPqRPePnn60QLC5eTBwMrq7eUrA9us8TcAw9vmfPHk9PT3L23bv3hTx5mJw5h1Fk1+mePT+r0k+MK6MgZozXr579DGUa0Xxi3eVyDvYMBwf5zZta9F3duXMHTDXoKV9fX1Tm+Kt9+/ajRo1C1UrEhZqxRc2cCcU71q4s5napGF4OWcUw4xVfTniDAoUnMMuXL9cTX7ZpQx5Zu9ZyMyqbN4fbPL4LhqbYsCHazn4XYHvS5ybyBFiPEHju7b2gfHmMRZY4lnCS5s17et68t4ZgBP36DNq/sJygwqLhJ0qdIbHfjxw5whtp/COLF6uzZGGQa0+p1Gk0YJxrevZUYRAzXaiYDh10O3bExsenWWjJhQsXurt7UKpHD0/P6WXL3hL5FEuWZOAnZsxgDx3SmhMlBPbYPY+uXEmAMVy9+jQ8enV3P01dIe9slalWc8hqHXHuGXHT5MuXlpCR0yb+6NEwWZasDqHwW9HRqXaUU54sJwz9yiIf01OUwGs9TT348FDcoUxZQz58+IDQFFjDpde9Vy+y3/XrRygc9u/fb3XkBwZqKCmIIlPWup2xO0H9gEb4Q23lRBdhxiVUJSI/WNo605KSFIjXNwwoEp/AI+k5hQgKH8dVrkqVQ1BH0PutriGKWrVAzvm5c/kzdnhz6dIlO9bk2bNRMciIGNFQSgOepNH42QMH4mrWVM+ZQxyay5adptFonsHBz0w6NFFx2rNHI7D/d6NjDnUGjOJlU0itw5JJxGmZp2Uwy9uLFy/4p3CR9PHJBDKVf53Sv1ND8nR4cp74CEaBpJkhFxdv2FSV5NK9pyRBL9gMTk4ca4JnGnQ1DP4wXnzx8W8V30JJ+AB54bVVsxW+aq5sjvdPmfKcnqV6JCUlmbTXh7wcIqXuRYqQ8sjlUbj929SezZopZd0WEeIjOeHxdZY7/87+bnLAYTIRmBUmncpmYy3uw+pvAPJJV0MXI8FteHg4ev2RdUSYUVi8kVA+YPRKqgYNwg+rVSN1P3w47tPHUosWIVWrTsO1BhQ1KX4aKeMTqcfX0bhw/pFnz5KRrk52sRTZ1p/o80qWZ8svebckKjVKKOHmzZvYsyqVClRJ0CBh4bhw4QLsrEg9dveuFctk6dJVIKFixXlIUPN/Ufr1u7VcjlGnrV1c/uza1QNMK1fXMEGSzs+k9IvoSrU3bjBOTqdkFfAkSphwxu66d++uKlToQLt2fUaMGMFjsfQH1h4eoC+CunnixAnoRDwCHjduHPJ/m5AJ9m3evDAi3ILr8Bzbd6YOITur4QkkHgHNnTtXKOTatWuEFmPUKLIMOjhwjx9bCb3w9X0ky5ktyzNHRzG9uvR+ZxcvJtOzcGGeGxTJTAsWVFqFObyePHlAgwZQZmM0i7l+nzCBGDa1as03BiMh20y9egZsM6JsmraOpeTkZPTkIckgVHH0aBVq5GPGqESmNMMQj2/r1ko0CTDqoH//F6dOxfNNAcbJ5cvskCFzYf2nBrl7lSrTcuS4ifeDRVy7tqJhQ2WdOgp4LzQAQGbduprhw19u3Bjz5EkSHmiIgD2fMo9AsqPjM1fXbujmlMiGZHzpGdW8tkKhXxp6c9ISE4/kakQUwQpy+8q5KWYT8mGQvZ5JRvatKcx8kvUystcnriHBwYlly6p27LguyscsRRqYZ1CvNWsIrN/Pz8/qPIqI4JydYSmSh4Vxn7jWHYs/hqScv6l/s26VceqmSsIf78q5CvMbiK64Q4eIGf/dd1bEMYzc0ZFxdtaxGZp9TEwMzQ/e2snpKc27rExNtbSGcM+ekdgPZ2fQxGCVBh26W7duuH7OmTPHJJmshXUJZh/86MqVGb5X7c2bZIEqWNBqe0ZGRnbs2BHji8z1+7hxRFnv00clBCmhS27Lli18FK9+wH9My6PIU2JDCR6AzT/VtKmSwufU/yn9NisWf2n+wgMUfESRPz90cOrbt1ZlcmFhZCjkymUwhmk6G476/o0GxAfcyczJRGbcTZpNxoWcwk6Br4axegTOnDl3KHnTAGNRQfFBcGc7XTspdcetJTExFR2KItS15fbsMOiW7F5e+K1l7DIoGO4s36u+V+gMOLbl8uTs2Ykj8/LlBFv7SATyobtyALo5hYw9mAdq3rx5JmVyajVDw4kI9xaUI1s27uFDPMLLn59JTk77xLEE07tDB+J1dnHx9PNbwzMefvr4PHz4MIgdMmQI1h1Mpt9/fwuNSQ5YGhEwWN7wAg75gx1/+K3Es3LY/rkUuXxVvpe0eiwKJveFV/xz5cqViDvatEmFZphVcAvvFl2yRP3/VfrJkVF8vF/durxCPLBpU0Lh9/DhZ1X6RYnJlD4+8KNjZGPJwu3DZErdt21TNW3aja9Xjx49pkyZAqMazDOT50VXrlxBcichWYoQI7tzGNH48zB5WikJH7l/+Hy0BDR79/LlBAODZ1PN8KTGx5NsZ+7uIU5OakFycbMagJ/fKpkXSV3ZXGt3vyvq1iU2Sd26wg8Rsmxu0eAv7Zo1bq1atXFzY1lJeZqgwRo0uEC90T2MWaESE9OKFVMiAhPvN86macdY2r6d0KONHz9eodB17KjCFB+WJ9SrVx9WrYpq2lTLq+x5vl+V81z1qsOX1Ko1DRR9Xt3PnftWzZqKAQNU/v7qixe1QisC3sMn/v4a+Bbu4Q0J/A9KeYsWWlxPeGDPp8wjUPFLlADzlaitTZt625T3QHhhnK5bToKVfU9hUQYnb438iSO23gX7yjn4xWCo/dJ3S/kzcxITPPaug9wBFs/4tHgTASebNzNVqmiM8r4Zd/S336oom8osUUyz1eJdvcpR9ndGoVCK0mVYmEeo9m3YoPmUte5ywuUcTA5ok8mvJ0tszIfcwxKqEvDIhNdm4wAjv/+e5NCQEAnGlC9PVKZz5/hnMRKmbt2RsF3DiII6njtnKWZPs2ULWUAaNhTAbpUrVqxAIg3QFjZu3JiQkCBlXWJZDk/bRKy1DGU14G7dsnzCgwcU06ZNs9Dvly5pjR1GDx48wCMydO9iFC9eLbUt6w2qB99iHBfeD5Ye2qsWTL7/lH6z10r1SmjlvpH6kBGMN/9gvskyltQrV0RcTmS0tWjBx3yIHrx9OxE6+7vvNOZkoups0trupOoEXy1XL0/3ne+hmepmGItCPrJa6lpWKx4WpkPPEDyFzvJ3795Jb89yZzxIEMI5Dz0kUbMW84vVVNS8qb3JP+LlRX7F1/eFfX0kBPng3tm6deubN2+KzGtkL41Kz7pnsCLQszlFpUqwB2LgNQtTc5SKlkr1KUrq8ePHeZi1l9fwnDmvtWihzETFV6VSwYIFVXv8+PGdO4l16qhxtx48+MVs3UIMPps8mZDAfltWsSPysCfnye/pLRUtNzIb27VvJ0zyBQYJaPyUzs9fSnYCBEC3b99DJotwd1d+bqX//HltyZIMvJqTGX/0KAnhrV0b+dr6UQjKO0ES2c+h9OvS+d3hlbj56VpbxvkySZw582Sm1H3GDBK03aKF15w5u0JDQ63KTE1N9fEhJIm3BJx0ZEW6do1xdpY7OdV9Qii8prBT5rHz4E1nZWd2yhQyCxo0QJkvXryAceXl5WVsVGDCqf0FC74eP95qM2q2b+8iWyIx04W5PmKqVyezUhB+p0vPgzFhwmvL0k7SMLjRLVtK7Pe9e2NhMLdo4S3K0sVfwgyy5rJp2jqW4uLikMulYcMLSLqyZ49W4vhkmGQ/v7dVqrB5N9Rq0qMJ1fZB3ffw8prl5xd25UqCQiF1zL9/nwb3L178rmfPSFRP8X/Fiqwd+6bJuu/fHwfN27QpcYJcuxZqn8zIyA8kf4IsJKxkBeO0Sr6t70CZ/crMsK+cmI3rTuIdvnlRefpO3gQ+3x2728T4rFKFzJ0qVSzX/dKl95SXIrxZM4LtYRhGet0x703XrkowRJG37fXr11bn0ZQpLOXJVdm91t1LvJdXQTx3w18Ot6k9ryZcxcOBfXH7TCxQsbFMjhxyB4cUtXVXkapjR+KSW7mSf9zPj0RElC69asqU19OnkzzfQ4a8tDCW9Jj7sWNFn8O+iVB49KScOnUqLS3N8rp0+LCWgvLFk0rZujUpZECAhfZE4mBQCXjqDnNVrlGDANg2bTKAhiKpv89cHz6KF6+R90nUYuv2rRHWgfevW0eUgWbNlJmyx/3rlP6FaqI/DXupd6KraAxcilJpVaZm/36yFjRubDCC+/Qhg2P+fONG37ePpDjt0uW5OZl/qP+AkviofIwLWY4hrtxznN4anjiR5NBt3txEOq1XH17BnfkV+a1W/Pp1jrIdk/TASKNuMsWMybqD+UH2i7v5uo+8naG0ac9jOb+Rf3Mi/gRf5fz5FS9ffrCvj3iQz9ixgRS66nb+/HljIb/++itPiiySqaTB1uqFC8k53alTJKV2rjzFi0ZQ4hqtHYra/fv3V61ahTyYaIRs27bt6VMuf34G/S6Z6O3GeGUfn/XIDVqhAos+jxbaFrjgpqSkoTuwa1cyrp4mPfVV+aL1VSywGIlZHNI5jMug675w4QK0oYuLR968VzjOysEOEgssXryK0koyhqzfmaz0BwZqsmYlDZgzp/ziRa1Jmc+7dkUt/8aNG76+vhdosCnXuvXnVvp5hI+CuvkDXacTt5zspvKXiZ9ed2RfdnFpkzv3haJFGZHD2pyEHTt2wFNTpkwRylS2bQvFWzOP0HwVZYoyOua69jrOR408nClUiPgjaHDhvn37kNjeWDKG0M2pVCnePNFexnZ7/VY+2V1ojfDwZDvHvEIhp4YKZ8i9c/Ag7r5W2PoXzCJe1VWVK0vpdK1Wh2mDhw/3F2bpErmr8+ZVUOCf3EI2TVv7fd48MpVq1Pjl228Vly5pbR2fukRds07NyHLjBr1mkMLT7jH//PmHTZuia9RQBwXFZ5bSD1fZsqpKlfxEWfNslfldkavEqO6xylh+nVrEXNnrUE+KQikqZ+SHSJJkSpFbiEtBZ3/jtXMR9mMi4ITiQhknJ7D5zdX9w4eP6JTx9ia5kJs08QkNTZZe97ZtlTQjioZu7hNBgjmWZ6HMEyfIHIERZd/4DEsOK6wsTFSOSB8MCbOpPZdFLSPHiYo8IEckOWbrVkygIUWmPtmRILG6mxs59mzW7Absbk+fJqEKkZSUZq49kZjYZNJfuDkkJARPNeGCN0IYsPH4/OUXlrrVxHYUO2ECzzRg8vE7d+7Axurh4WEBZiyC44tIIDQaDXExuLXKdTEXRvHi9eNywk3kNcdLKPP771WUfIz9T+m3R+mfyc6EsTvu9Th8hKVmfXJYmHWl31TGSvXUqWRwjBxp3Oj+/lHQTz/++MqczP0aws9aX1lfVEI5J3eUOzrLnVlOvwUOHEiiMytXPmWyhNmZ7CAHtnzLFQ8K0lIAKzFvRo8eDQLBMpbSnve5+3nlxD0g67pY5AAG/bKNsg2SAEyP9CtVWmku4av0Plq+XF2kyA5XV0I+HRQUZFIIgtd79+4tosbTUN+w/JtvdOkOMaW7+zZZE/isTBmFTRPj2bNnoA9hXCxeXbp06dOnDw8mXrCALPqlSzMJCWmZNT5//50oZ999NwzU7gkTXmP+P7DroHmzMdliU0nEoUqlJ99YsSIKZUIvzGJnNf2hKTwLqj+Mh5qKmus0+pxx/fvPRgKYNIvJyXlsz5MnT1q0UFL56s+h9EPP+Pqq0iEHDL4KXaH6bTUyEr3s8Eb/yevXBA+aLVtaOmHrZ1L6eYTP6fz5w7NkK17kGRSynOwMj5K3u+4nT55EWpgFCw7kzi2ngVlKKTKjo6MxtIvnsUYfRHjeXOXDy0BbLlQv1MeNMWUJ07PmKDtrFjL3Q9ciyR1vP1+5kgD2JLzC+0c4lRo3To2Ls9qMe3aTMV9RdjI1Jsa+Ma/Zu5eUqpb4ZFKj0RUsqDRJeyC8cIheyJ1bZy7TgRFcsHx59uHDED5LV/zRo2y1avDKy5w06TXNPDjVQjZNm/r9zJn3hQrdc3FpDYvYuXN37RifvfyI+dGybcu8Z/NqUjSZpaBnIvROgD1LqFFDn1vQPplpyck/55gMXTDCR7wLwwJI1gCH8BBZ9qhly2wt5764fcL4PQNnf4nrsKjCUhnOhRuMQ0omK6eRfkofH3N1hz0O84UtXUoiRsqX/6N+fQ2PHbWCkVNzGH2BWagDAwPNWaSi9gQjtkAB8uD16+RgSr1rF1OxIrxK6Xc2hS2tKo1IYLsTk/WK7EXO9kNq3nl0Z+vWraBSnzhBnH269u35lGrWTws3bSJt26oVypw79yF1aHaFfQ0/qVuXhCwfOhRneiyFhsopxS8S85ssJ0zzU6dO9ejRAzfu/v37C1M6CmUib5iQnkFfSErMqGjUyEwsRzAePm/btk3KmDdH97xixQoQUntUbYziRchQ526EtLrq+aqC/UiHfF8i79h/Sr/UQYxZsaa90cOw1LVrE6CwUfJUY5nq2bOJ0j94sMEExkDvdu2MG33cOLKXLFpklsHmIfeQcIfJ84m1cy2B6ddQ1EjHdqdQJhO3HDmemFTbyrPl4f5r3DXLFcfwf09PJe8p56nQLdfdU0lgJE0etYbHq1YVuxk4HTeJnYRUALJ1HvVcn6amflIf0ZxBHhSct86ChopJoBD5k+Hm79KF9NGYMRnevsOHe8rmk6ODUeFSJkZiYuLZs2enTJnC86h4eXlNnz4dFhGtYXA+/FW9OpmKfn5vP318hobqQP9zcnri4uIJusKFCxkHRJtjNotgf/RUnWQJuXcvER9HK6hN+zYuYS54jA96P37VoMFTPH83TnZojO1BxQhTz1pIHGu3YnH2LFepkoLSucpnzWIZRp87ArZhHvSM979buJCQdnfrJhSioSmo4ulO81kVIET4zKtQYWjVzagDbJE1ZXLm5AQaoa0y7969i6iPlStX6kjiZC1sAyAc2kGKzIULF2YoB2lpyF8xbzMxucsz5XkSsEHsIPjkF/YX2BSZYsXIqVdgIFgLYDPw2S0wc2qRIsr4+LToAwe8WrQAyS9fvrTajIMHk84aIZuQeOeOfWMeXWiqoUONhffv/8IycEij0ZCzLBeXCJkMzHsrDkWWAzsf8etCg5alXExspUqCEn4oVWoLRcFZyqYpsd/Xr49GMH27dnMwRtPW8bl9N4E1tmzT0uUamct/Rv/5NSv9uBojXtQmiAt/xR0+fEBWG3VokeRr10hKtVplHqEj2dZy/vzqZ2jA2W/FaSjR2V/sfDP4dqV6pcGwGTZsZ9GiA1q3XlqhwrYSJY5t3nz58uV79+6Fh4fzTpO3b1PRQN23Lxa9A1WqXII/p059I6XuR45oKciKwXKCBkkykIwcKaWPunTJSCPFVKiAgC1Fy5aawECd1mzOhweJD/Io8hAUqLbl+zQbkhuGhYVdunRp9+7dGzduhJE8ZNgQl3YuQuIBKPaHV6/03hmKULJ+/oZhskWLErjRvcRy5VZTORkRepjt28cn0mQ5NRs3Eo2rWTOr4zMhIQGKjfu4r6+vcXvysdHPnhkB5Z8+JW2bIwenNhEIB/atMNW3lPY0mdjx6dunLTq04NWYj+kJH5r0Idizt6lvUebx41p0L2bWfP/XKf2jVaOhQee/m6/fSGgihkTzCZwzkDyjR5Pd4tdfDUbwyZNkBFevbtzo3bs/5/ngzMlED/ojziBobL56Pg/7+UhpTGiklA9Ie/3aBGzGhSN7w17NXssVx3y0Pj4qimSdDzJPpCtPFuqOwB6wTC4+vY/4VJPC1z09Kgv+Bu78Nrzi46THdvfR+fPnMRynWjWSSyUw0KxDEdlIpk6dysvk7t7F1Ye7d08Q4qPL4/SIWMkjFlqYGKmpqbdv3/799995NhVYLMaNG7d//36VyiyG8sABDdUIGbU65VPG57p1aswPki2bvFu3cSIF3fu5N+GZjl4jFIVZQipXZtF5IAzhXaYm57DlGBJ8cu0aR9eLvRie+OrVK8vYHtQpHzwgOQ2gMLxn4tMXGo7TgXYLuj5iKEH7Tz9O140Zo3f8jx5N6E30rqnKlYl+L/DIwvWG8jK9HjfucytAFymrWvsmbjJZBGwMsE8rKlWSG+qaNsmEWYzokcmTJ/N0qH/+qXZwIARgO3ZYz/ILagc83rFjR9jMYgIDoTAh5YoVkZPz+vWa9Rm2vSaQPz9UU8NpU716GZl3KaAlVy4FNnjnzs9fjPlpbM2acMNxCfAepBzZL6sTa+jikj7mFRgEtWGDGfy9vEULsxi8gwdJzOhvXl7EklmxwgqMc6GaJhFXow+CH96o9MP/uHSeRJZl3dzaUsLv7Z8ylkABwJAb+D9lymu1WkMYSVq3BktDukxYhdzc3Vq5tWp6oCmo+yCs2/NuX7nS/zGdYw10LHsw/T17RsgcCud+Au325IkBPd2yZeS0/AdfjsmeXe7oyFE6Y+nlrK+pDw14/r0YIIrOfsf+fuQcQOlpgO0pUQLpoYwv6M1OnTr16dOnXbshtWuPgc0HMyp6e3tfvZpAafzk8MZq3YWQko80mB7HiTE1n3Ef+fuTHadNGyV3+TL5PUdHBj0HoPqXKcPOnMmZwiyUVJUkGGBl/qjUKMv9Dvr94MGDx44dO2jQIPRQGF8t27esP7B+r1964Z7yetUqkr82nQzQet9AI9NTzijVy0qV2Dp1RvB5LfR+WHUKrIqwq/LZ+gwA1ZgNYMIEieMT1eguXbqkGjoj4eatWzU0UYZp3xZDgd/aM2eMVYUulD/6jpHjw0KlERfg4aEUlnN/3P7Sa0sj9RMWb/r06STcK4Cgec++1wfy4oAZOJD9T+m3c/EapCKesBVRK/ARbcuW0LUJhqQWppV+Gp+u8fcXHzalU/qIHmzYkAypGzcSLMiEvZnkZdAY5JPvp+pHsrKp/VAm9Xy3atKEHIA+fmxiXegT2YfUSG1lF0Si+lGjWH4LhBluuT15YA8KR+57k4ogoZUsdbHQ9VpIKbMzdqcdfQTzE3XuOXPm4NF8/vwKc0j0qKgoTMwZGalPz64aM4b4ALp0EenTIKe27ABh4BI4ooTgvP79++M0xmv06NGgc0vJ9wkXZt8QuiVsGp9nzmiLFdOTbDRtqrx6lUMS3/Hjx+tPHtIScytIWkTRKX9CQhqCSnv0AKtEhQs0hvCyHIuZFO9yd8eOJetFr15KzHjF8wxYwPZgOdEzERCgyZSF5vnzD66uSqwmLF7GwYhLlqhBt6b04ar379NgPhJ/cMmSogQa7y9dIgpfjRqfWwFS+Ph0btoSiYzmzKGJ2GjKd5bmkrRVplarRYCNr6+vyIbEBR1sacwHaVkOBt0eBkOUkoZNPN4RWrSesp4IHOgsdwYNJFQXyrEsqAIj6tQR5oJBRappU22BAqSLffMvX1+ypDClg7nr9GnicCqa6yGoaG+mT7djTSYcx1RHMckNGhOTmjUrcbyZy1QFdguUc+/QoVZzAIGpj9MKDAmDg6zu3SNAPaKJBlUlSqRGRYGmBVoOfFW9+q9gkYpIPKSPJRi0PXpEIlEPn8EAQ3RAIZYoU61WY1hn2aVld8fuVqeoEUXN4zG+WqUfE4jaSlupo/SLqNAP6Kk0Pufp1+8FZvl93rkzHzsnsZwxqTEwC5wZ5/g0E3zcxNlf4LZDuBNMFpgpPLbnZo4c7q6usK1MHz9+SvXqY+rUGdyvn4+PD/QLfGhSCYb9AgROnUoiUMuVY2EYWy5bw4YK6s/S8O2JZPOW0bb47L17HOV1ZeQdugTlz+/TuvWJgwfZWbNgmqPqz+TM+XLkyKSnTzOOheP2Y4KtR4mPzPU7ZrrF5UWUJwRmx9SpU8GcgwUkJCQEtl0ETYHAvkNJ7qA9Li4kpVq6F0BK7yhoFrberR86OT11dSVszKI09i1bkqVm27ZYY5kKarRrDx6UPj4xBaEI4QM3Dx/O0uhB08q00tsbOQBF0m7duoU4QJvmUUiInn4HubDx/qlvpjo+c/Tq5YX5RqFtwfaD1hgRMYIgNt8tRJl16ypoTlXNf0q/nYuXj5KES/8Vow+K5WiY9nsje85YprJVK6L0bxMnrJbTyFPOaMYWLUpWMa02xYJMH5WPcYIM2MXhw/2a/diRmEDH3X2dyeS+BJP6ehLc/yv7q+WKIz8GqP7wyNatW0Hm+vXrLbcnAnt4XwjS6hnHpaGCDvV9/i7O94UvwkvGvR6XkpYivY/u3r3buXNnjFZEV6hxEhnRNXfuXKwFNcwZOU0OIjr3b9OG9MLMUsRDrDZFh4z8Noj8CwwM1AmSGUm5goM5zM936dJ7W8dnUJAW7ShnZ9jt1Oj/lcvlOPOjo4nqcDz+ODTmd5rvjKWFhSWjy3b8+O3ILM5LbqdsR8YVuwgTd+/frwGlBw2Dy6bsWyG2B8vp56fGXEKfvtAcORJXqJCS0tcyuNWZxovv0acsbdxY++T7kdAub377TWycJCcr8uQhkfda7edTgLQ3bjzOkqdBxUmUMkuvZ2ioQ8tkplurFyJzYHg/NlJ2odM7dFBS6DmJnLYsBzPTDaD0F3ebV8/D5OEXCuHVQkkcRQFqQj3xZNEiUGI8XF1jKVUXdG+lSixCZq9cSchGD17GfTMUk99Zzsg2fjwlD2lxHp6JNMySBhfMX5hB8GphzCNgmjBrmemjtm115s73Pnz4gANYsXatsW0vumbNYilHrYI/fufN2tN58z7v1ElLs4y9HD7c398f8egdOoRRn4jKjrH05EkS4j2++UYhzCd69epVJObjE2NbkBkbG4uwgRq/1CirLIuxpzXVNaErL7y/8JUr/fYlqCJDYulSsnu6u+/ZE0sz1HJCsVWqsJhdJAZZGg2DaiyX81T8KYJK1TYxWWB09jsEkpmyVLOUx/ZMq1oVajFz5kxdOl0vj+yHIQS6qbv7vbx5zwwcePrMmTMBAQGjRo06Sk8jk5PT6tfXYPIvCwULD9crf/CGb8+lS5cKeSks91GVKmTN3+7YqGuzZrhz9e7de9XKlXdXrVJQ/Rv/g2ITB3pkylt9QmLDg2LhCeSGDRt4VjpPT0/Q8qFely5dErq9RA9OeD2B5JD6qwwJlq1TByyN1NhY6f2uGjBgoaw7zSV3kLeajEMm2rcX78WgZckpOl5nhrHXZNNt2bJFxPGNMjF1z759prck9Zw5xDXQu7dJraPp6qY7YnfYNI88PJQ0gZ2aLyfm4v3j9B+4/CJbw6+//roxZiPGW8M9Dx+SeADQE6zSdv3Dlf5L7y/NeDMDXu1YvDqrOkOD7ordpX+kQweCIjATMCqUiUxz2tOnxWYrjQrQGEpITEyDrnJ2ZkwC3Plnf1P/hnz8GXghnTaHnNDohunCsCMx6LZHj7PmtsMVUSvg/oGslbz0Pj4qnjHg0KFDmNXSQrMHxgQisOc+d1+vTND4zl27tIawP32UCc/9vDpqdVYmK+ZBvJ94X0ofgTKE4MixY8fygXQcl5I/v8ICyCckJASzcGs0GkQyKOvXNwTm6RC0d38licthihVLMzxCBQ0YV7pbRvgu6Ruhn99bytassRzMIJL5++8s+rah9c6eNWjSn3/+GUp17NgxeGTES2L0z3wz06TAzZtjaJrGH3DP4CUsUpM0ao3veiEWEHU57HRo57g4fYzU+/Pn2UqV4FWI7cFyYuwR2DOW1xrL9X3/Pm3kyJe4DbVqpXzwwIob9eJFLZQWbi7lcOmkQ6VkUycz6POLoUCCz6QAwTbfUbYsb97T9Oxen6WLCw7G0GML2FmTF57UeXh4XLx40WTZ5HIOOd1cXa1kp0pJSelO09Ac++abITeIm99d6W7iTI8lWbp9lERZ2bFtG9z/Y+3a0QEBIOHEiXga1K7CHwocc8xBFgH/O3bsCbfdMKQrEV0YwbJ9Lj1sqV3bpDvNzc1t4UIDHJ3BPjptGtlH+/c310erV5NTiO7dn5ub7AMGDEi4ccNkKDB/RUToU9Ft3aoxBrDNq1AhavXqpCdPmKxZdxcpgtM/IiICqVHy5GFsTX4EGj/a3vD69GmSaCzh6h1Auf8sXKmpqXgW5+rr6vTUaVnUMpQw8TWJQIPXr1zph2vBAkK8uJWyRUmXiTmeYTpHRaWiNgxvHjx40Ldv32vX7tE8KyS5Suq7d8hOy0nASmE5MVe9BWp54uzvSZC0LgoX3G9ulS3rTj3PmBadZ+xFGp+P6fR0hQop3741sdaHhibnyMFYptLfvJkYBo0aKYTteerUKQvHsKL2HDaMGELdK/ggJz16yvAaOnTopkWLmGHDFDQnN/zvu5wc1Ddnm6R9FIcDqlQq0IMxIBU9PqD9m7NOxQtRWgps7llCsrh4uri1avWoRw+bxtL5catyyB6T6KARizAjuEj+q1cfcDAgnjljAVm3DmMYbBqfOpqM3MvLS0je/+iRPrjWXMIPvYeialVRnADIaeXWKvvN7PU09WyaRytXqqlLK4NQhM/Fi+fAmGIMzK2HSSTasyJb8SPhgzHABf17lX7Q+KFR4NWOxau1sjU8GxSv19Gfd+9O8J379llX+ikFHnf/vthspVqIxjD6PiIi2WRkkkjmRs1G0c59mbsMn5RiSvHeBTLIWrUaN44o3PPnm4hyw/O7tsq2VipOM88FBpKNENNhmKTw0x+ApHDfKL4RoYaQN2rpUoMVbeBAluorBh6a6wnXMQNISVVJq30EhUEf3ogRI4Tgh4+C/JHmQD54NL9/3z495Npwc0UgnZubkrfZUPXBC3RftDRMRrhK3wgTEtKgo63SFmVARxS6nj31KHZYwdVqsZKBFv/kyZN5OObdxLvmZHbpcoUyebd/9iyj6YK5YJKf9UkuWZawceNYfizhAS5v7LG00VTlygmxPXw569UjA+avvzT2LTQPHiQhYSJs20uXvuMkZfjVwVrcoNw9on5leSx0mmbAuqjHPbJXr8+kAMEGP91xMDlDzxnepUtGli4yhEqXxrQy0mWCNYvU70KTzPi6c4dDy3ns2FeWBa6hI3ZMB3dnubOj3PEcd85Y2jntOSTx5A3IzcWLq0qVSktIaN+euNIXLtQvIy8GDJgiGwKfVK8+nc8GbfK6dYtDnVj1JJzYzzlyfBTYuO/evUNyIQybg1de9TfQ8Dw9cak010dqdQpmpU1MTDOybwm16IoVK1LfvCEFyJ3bXFGRzrxBAzFb15PHj4kV16RJUkQEOSibMqU9jWDev3cvlrNFCwUNx7SBvefMmff58ikwCaMIj44yUZ/r2rWrZVKgVatIJuwOXTpkv50dFl7k6YLr/PvzJChfXfPrV/rBYkS9U7pM7u5dgkrPnj2VnmrCJgItuWdPLGj8FIfdE8/99AIxlmPJEonlbMWRRHWH4w6bKzBx9he8JwvL4hjh9Jh7DEqe0M2vH7ECZz+/zgcEmF3nV62KwiyQ5nBigwapaD4KVtieHMfhIJHSR1tnnS9ceDfOMliatFotjLHp06ejnoCfT54w4cj48bs6l3KIkDmHyk7VyA5WeizNGgu7wLVr1zDtNF6gcR49etTyKZ9xeUAxzcpkrforabG1kyZJH0tKpa5a2RBitxTchMfsTwVgJP7ClQq31Axdy9fXOK5SyvjEje+MANCxdq0GXVHmzyNUxM50dOQPMeh8PwNyGgxpQOgT2PI2zaOICC57dnJQERxMlCVhLt7Q0FAEj3Xs2DEFrrSU7Ex2B7lDVGoUEl38/jv7b1f6A6IDoL2GvBxix+LVTNlMGNwTSYn2Y7dvtzLZNBpCFOXoqDPKzY5QcnbiRMODeJK5w8WFszyBUcUvoyjDf7JWs1aowbMsS4nbfUBtAoE//WRCJ7iVeAseqa2obbniqMMFBRGlHxkDxqUHRBpfHXUdxUFOOh0CxH8u5Kf+6y/85MQJLbSKszNjvOHdT7yP6TzAJpGCI+wMtpOhm0FfEosgnyNHjsCzw3v1InpAiRKc4c6K6EkMmUcnAVuuXFp6HmLQfYn+NGaMSS5LmzZC9ADBxm/SAySUefOmFt26OXMy5hDzz549c3d3B2Xx6uurxAJUlbIgc/bseVCLSpX8RIE+leUkYZOs8fZr1zJowsCmArGwvjx69Cg1KoqhDqHTefOKuAjSg0BYSkRtW0KQ4MTgsmzZcRsvgK5PtUk1aP82tWdEvWbtZCuR0oeHR/NXcjhROpWFCoHS+TkUoL0ek7LIwtBdx2fp0s/0Hj2I2pHO425V1IsXL5DV5A8JiSoPH9bCFkOtLLPB60mPHt3Nnt3D1bWVe6tst7P1UPUwJw00fuj9Y+HHECoWWq8eiL7/2zrq3GJ4PgBVyZLw+Yjez4oU2UGzQf9o/jhLzVNNI5G5MLcJJrKdOnWqjkTQLhSq/g/44EutFvMEc8HBFvrou+/IZnziRLzJbRsJxxDIxz18aCwkLExHf0S+d69G1Efvr1/3btoUjVuSTXMkSYIzrmbNNzNn4vjctUtLSY0YlUrSWOKJenr2jDTJ25vuFhmILnAdZXtT1KypNvRNICcB9FS3S90wVWrGaE9LRt4VPqTnq1X6k5OT0XdjbOyZu/DkJzI9Hy3StgwYoOT115Il148erd/yojdsIBPf3V2KZGi3HEwOUJvepL6xUGbi7F/vBs27QL0geNAg4uZ3c3sgCBcWOvtnz5Z0oovpKdHTZHxVqMBgxhhRe+JCwRPyWuiji83dW7b0ogezGw11VNX+/fthT+d551y9XKv9Wm3o1BrhMO1lsrA6dfbs2YOsd+j5njdv3p07d+zu991hy/Mdz0fMle4ZYbJWRSFfcznZmQv5i8OznTp1Mrn/bt1K/H0tWxrAOJmKFRFVYev4xGz3kwTGSe/e1pnvFXXqEOy3IIUCSAA5JTaUcJI7wbBRpihtmkcYAQg/yvtqeVI+PCnlQwUaaRqRWN7Y8wh5vX2b+7cr/UHxQcg4a8fiVVdRF54FRVm/MQ8axKMFLEw27v59olYWLmxi5Vq8mLhLfXyMcRf9+r2wPIFZjoUVBYwJpU6/RiC5EGHco9fZs2fx4G/nzljcXUx65YnJyBS2XHEksLt+nSwryAQyZMgQC8Ce/Ir8PLAHLyTE+F72O2Yr1Gp1deooEAhr2isZvQbklFCVEJIGGOMI27ZtC1bNhQsXTA5iyyCf9+/f66HquXKpfzPIbQzqNerWcjmHOgcuGTGBgfR07xFyJpjLUGbrRujuzvFpGRLv3WPLlIFXkczt2zVUXZGXK2ciE63wgrWbHH0cINiekS/NsrklJiZi9b/55qLoWLn1GfJs0aXDROVE/QwWl9f+/kSFrVJlXsWKJOHR0qWiut+4oQc8sKwNC02RCJKwXXa5BB0YrzDVgPT25M6eJROtQMEpE1/gYcjkya9FmwJYboRxy4zu+CkLouYWKMvX4UdH9iWEWnyWLnSD6Wd6eqYOy6ISEhIwPm/ixIkisldzF/JrZc3KIAeIiZlOPeU/9iLB7pX+qHSbu205cmnYjmEYFI65jX/IOQ8TPOu1NEpCoCxaFPbrTp1gQXBzdW1z965phbdZM0zBoeEhGfEnT/KDEFWWhw8f8n0tVP1nzpwJipS+Z0uXttxHM2eSgMiRIw1ScsbHx3vQC97An0pqw5gM5vv5Z5ZSACmM++jtrFk41FevXo3ZNHt26fLQ2ZnJmjUpHTRSq5aCnoSoLY8lEVGPuQQYeP+BAwfQcQOjCPMKwasA0nYRG2rL0S2gSWRlssJ6LhTS7Xk3IXHnV6v0w4X5UBGbLkUaQ4My4w4f5oFSlHDpTxCCR7guLm2WL9e7gT+8eiV3cmKcnXUSsgZeTyBZ6mqoa1guMMMkO3kvIUFToU2mUZKrGQK6Z6Gz/3qnYRi7dflygrXG/IB5G5FYUxQAhisqf7rLP4X5WU+fPm25j+Q7d/Zu2JDGnU8y5zOKioo6ePBg5+EZsJ/OXl79Gjb0dHHhYwBA+48zlZfj7FmuZEmGp1az3O9vpk/vsUDWyKcRyLxy/YqUsbR+PS5x8qCirZA/YPbs2SaFx8am5sjBgLWiVqcY6GC5cnHmD83MtV5MTAy6P96+1fNrY7Tb6dOWVmZ24EBhDnh4FiS08mjl/NC5roaokaujVts0jzZtItWvUYMkSJ36ZqowFy9YX7Ap84xACOsdFbzAZMLgf6PSfy/xHrRIHXUdOxavygqSlzskSZ9H7eWIEQT1sWaN5cmmPX2ap+YUY7/27MFMvcKnEOfNE/daKGcFpgJJvqvVH9O7KYnjYaNGb8SvWbMGJkZgYODFi+/N8dmlfkwlCUzkDmBCWKg4JgQJCyM7SmRkJDp3LQB7tsRsEUlAiquWsk1yBwfu3Dlkcy9RgmjVJquZ9jGtubY5n/TbbhyhZZDPkhkzyNpRrRrhuhdckyZR7GP3DCVGvXw5cfZXrZqcmIg5iUEDzqyN8PHjJGRte3QnWlmwIFEHnJxgWUylAHpQC+bMeevoKEfCNau4YcTfNx9PWg+zHZu8Tpw4gUfqc+eqkQSGdwnUGb6DKP13q4jKmZKSgnVfRjWn2AMHutO+uCagI+AfqVkTmc41Ehea4VfJDkpQ4nLZ/LOn7GhPFTXCX/34IzyyYUM0hj306BHJGw9kztI07G+tZU61dUFMSUlrVuw8/FyTImfwPI/P0oUIH+7qVbIIFCliVWZaWtoMOiz79esXGxsrvZxjx75CBn2WFQ/1+OPHyTqTP3+bc1SZ7uRhATESoCZnoS5jXXj0WnjjVnllBDd1716iHii1ciXxs/bpQ7XqNBcX4pBu2PAoY8QH/eQJh0makdAaD9mjli0TnraNGDHCeAYJVf8ZffrczJFD1bOn5T66ezeRBHWUMjDFr127hjgE/TJCj1w0S5cahQZxuXIxeJ5p3EfaJk3wUAtMFD6bJo4lbfPmOmrXBQSoKSyTsWCmmSTqseQw4jjQ+OF3D+zahWdrTPHifCwTYrLBDvnp1U/QZb4vfEVCRMSdX7PSjyFSSDlvVZT23DnSFPnzpyVncBOVLats3Ji01dWrVxs0mE7dE0NT0s9mlZTv1SpbKxl47xYK9x0LV/cBIbIn2XLeyOXu6gr/HxjBd9HZ38FhBaVBk8TStmED2SizZwcLgTO26oX5T/hH8LTH39/fch9NpoC09q26OTk97dVLaa6PniQ9Aesx582cfn/5oQsZr/GDB8NUEp3oZtRUq0Pm6CJFGCn9zlas+DCXrM6KGsQzMrm71bEEexOews2bp1Z6ev5cq5Zl3nAfn0gkdNIrWmvWWD3qsdApyP21jwK55fJkRGFZBp2qly0juWK666uGec1rja0FbbsyaiUMsPa69jbNI5bVn0OGhiZjFK8wF6/wWh+9Hr6tdqI7Mi7+p/Tr02sXUhayY/EqxZQSnsu8GjuWbGDWJpuGJppW0rNLsW/y1i0MEhU+NWTISwvgP+HjbZWk79ep9WjaIkwR+POm9qbQ43vjxo1nz8gwrVDBdJp6TLZ3i7tlYbThLoWD4/3793jAZw7YA6/G7XnuhALzcUJ9g1t0weGL3mVzrYerj2OE4/oL6z8FR2gB5HNv0CBSFzc3hWHMKR6k8gzopKfUanQSB9CYOV9fX347yZSNcMwYorG1KHSCKGeYcJXyTmoDtnfqRJI2gNI/eTIrBd3+5s0b0EtcPF3yhuZNTEs0V8hRo0bxeHEvLyVlHVao1dz9+5xj1jAZLMmUuFNUTjzl8HBxuV6pkh7o3LRphINDwhWxtwZKa5w11mTdQRPqPe2aLIQkh84R0Ale62rqYrJ3G9pTqUQurKR0n/HZsxmY6ZAQPYQsjiaj5VxdM1cBGj+UDJiisuv3j2XMIxHChylcmPz01auWZeJxSseOHTUajU1j6cOHj23a6BBFAIp4hsQPH9Q0KCUocBS0bSNf4l3bZZSMk7+e6p46P3EmYXZubjCWQMDKcbfJ8MiyP/WdHtD/vGtX4SHn0qVraW7RhWCUilRepOdyddUPA7WfH6G+obodKBDIOSNk2jYM7Xgwc+ZMVP1BqZoxYMADM2zr/COg8SNnC/8JMpgF0jM6om1MnCjKwbdeu766orrn0gDMP2gsk0QC0ESePbqjkavPppkaFaUqUYKng4SKg8ZPl261uZiTxo21xkQ9VnDYlC3Nl6YOlFMUF3f2rFKpRPP7p59+epPyBpl5HyWJeRVFxJ1fs9KfmJgIewoMuRcvXlg370eNIp1omDVpwIAzdGPqGRmZ7OQU0qxZTyHLHPQR2YXbtrUqvNNzsgRti7WeTeLGDa3DmrZVpxFs+nQzlFC73Qlfdo4sodLzscCaSaiiaytYNmO579pVKToBEK7JUIAffvjBgswNlAHWy8Vl15arIKd4cdPZmtI+pjXTEgzziJd6Oxzm5sAOHfYUKvTS8Gxf9CCu9uiZEh1TmPDE05y1ysKFT3InXKnBdPL5SQtjCXal+vVJ9WGfIsiZn35q05JwIr+mKb1MXocOxeFKqB8wFIktJE22aXxiHCP6JkAxk8JNxyFzdOnSepfW8OEgofDuwt7PvUEFdZA75GBy2JTsDC6EFU2f/oaP4jVZ2ruJd+HbbBcrIPnef0o/cSE7M87Q6ElpSbYuXgWYAtCaLz/oj49fT55MTnAWLLCi9FNmMZVhXm4e7k8CPhwc0gSx4bhzHz8eb3WRRTzPRHaiLj1Hb14mL/8t6A04MWJiUhGsYlJgEy1J4XZYe9hcrUELpKyaDD84ML4wOTnZJLBH98EELjNk80FCUuH4mMmTx1v2B7x3d1daHnCxsbE/bP6hcY/Gn4gjNAfygb2cyZlz6Hf1qJtk69GjYJ1pVq5UjxjB0o1ZLgrBiA4IuJIrlwdlYoZ1NnM3wrdvUwtkJyFKa/P0SH72LOH6dU2jRsdllcvIzhG/Qt5woQViVWbPUWTD63Sgk/mzaQaplDH6OTRUV6IEgymuMCdDsQPEnlykXmTcnnNo74/o1g0pTZYgCX3VqshulBFzcpnDZjSONhbKfPAgqWpNhexwDaKPnu/7PjWhrKosvF8bvdam9tSsXk08uA0aGNiNhB2F1KtwYT25DShqeNDPRURklgKEURlZZGH7Wk8SPihC+Kg6deKjCc2JunjxIowud3d3nhnaprH07l1q5cp4SPWcx41EU55KtkKFRuqG0LCj9xNOmEGDBlkQ1WR3E7in1/BeKKFmTTIklss6vEGSkA8fFNS+SmH1uw7G+TRqNIDSDhps+e3aIYuAXg/WbN+ONIu8D75Xr16pZpDO+Ago+tPq1gXdAL3+33///eXLl831ETI+zZyZcUyK3sqQEP3xrAZZO9u3558FjR+axeFoNQcHuRCckLEQ7d5NyuzhgaJ8fHx4fyfakLCmYVI/BDHWqmXiSJ1nlypXjhUR9VheQ9RqNSKgDsMq1qwZ2Up++QXxwdB0crl8/jtCI9NG18akHCFxp4lZs3mzokoVDaUb/v8q/RSdNRP9qdb8/FqmeHFyxnLkiPDxwYOJO6ZZswDYOqmdecGdXshhzz14IKdZAy1PfE7HFVAUsKBRiere/LeFqLbeM+Ljptu7rnolEuQzzvEnk3xiJmWGh3PffqugYXhs+oGPDkmlrl41MT6TkpIw2goBbCZWlQsXEKp/4McfQVSRIqbps+FaHbXaGFWbRFPMKvLnF/LXiWKKnJxImOm4cazxMYVxedQU766pWxfee0/yhoLVXVs3JjXGXKfArkQ5Ohk8jz/l50eOcegaYjaEKSkNTGsKqSIlUWC2rBMn7Buf0MKYBAMmY8+eeIagtgY25Rjq2vzw/Dk8RfBm7VwcQx2RBqahhizFx+KP2TSP9uwhpz1lm93go3hNlzYtyVmeVRbumKfoY3Ob779L6ed927YGUsCVXU6ckXzCjjczZhCogBlgGS+TnTJF5FsywCbS4SjMiFG1Kmsul5aonP4afyiPt9Ib3u/QEEhGE2UTfqdEIid8ConhoqNNbK49InsQZm6NWWI42AgpXDKD0cLb21tkZwuBPSbbk50wAZm2tvQkcZbZHEOvXzdLXwjLdN++fXkkD+j9oP2bxBFKHMQI8smenRk06EWfPpFeXrqGDTXlCj7MJ7tbtAghqm/QoH86SbH+f/364p07NSFhSGNigfzx88+ZvhG+W7TIT9aHUCIWf4aBfTt3xOTMFk7iWWVHLspKKbt25SQbPK03Er180LRB5kq4bNkyPgsvv3AT8mkHOQIWB50kZ9ztlO1E5UyWyx87OyPNM7Jrhzx4ABo/ocZPD2rkL6SFFvG0ZniV0j4uXfqOxOz+MpKQNUWUhXWf6NA0gUtBZUHMJS6xPfH4XsiwhFdISFKOHArKeqEfrlqqORkrOvYtiGFhyXkox90Mx0FaQ9pK0PURgPHHH3/s2bMnaNy4M3nz3vT2Dg//H3vfARbF9b29iNgVWyxRsfceexeMPfbeS6IxdqNGk6gxGmtMrLHH3hso9ooNu6DS2Zmts6JYQengd849yzDMzi5L0eT7/TMPzz4L7Ny9M3PLe9r7hijWn8HfacwfZpwwGRtL0B/a7Qj4Jr59qylWDPq358J0uKslNSXfxL6hBycyC1kevWYiAVyfzRibvnwZkwNLFg0JUmXn8+VLeP48hsUndZUrSzdFUrvLm9eX+aLMYIXnTblzIxp4+FCQxja1n38OZ02ePFkMmttKcWGZUXdKlwZQSDwVAHF2794tjfVJktYQ8NWvby5dffbsGRm3CcmEpsZz5xDBVK9uhtSC3plzxhnvm++r3iGKz51qt14vX05ifDI1TQp6aGBNwYJIM6KSjfmDB806Ek2b64PCnoXEhdyOvg1b/u6I3b+9+q2mvqb7O3cba8gGhnK+a9AAMDp810om+woX9fDhQ51JBxAN+n8+SjmlW0rcqVBuWLUqcQv+G0D/5cuXKXaRhnl/+DCJyErbhMGA4c3WHXLkePTDD1gyMX36iy1btlAaOqBhvNgmTSxZ2mTHZSNSHrloXey89qnfoAld9eeq7ncUKGuJAq503nv+qpwwiuy/nwSj4QfemJgOI6Fea/fzO1ZZDra3ZYOvXr3qyWQrl9apg/Q3JlPfvoihf/1VDlsfCg8L8AUU80YAoGMFhYSqLiUwGGB2GE2cqFUMU8i9rtHRhIYjDx2CX697I4Nc44GNRz1TdkPs32+ABQT2JrGCeQWrYVhev77tO/n112j/gx1iyZicgfFJeinbtm0jVQ0Rvdg4SEEcbtrff/+Ng2RO1RKaEqSh8cvLXzDtPnx8uuYRdL94cU7V8S9pFa9y+sbDuki3OuVwlkf2/n8F/eTbvhl9M12Ll9FkRIeQ2iFlOi1ahFjnxx9tT2Dt6NGk7qQMVphu13sm0pEmQJf109PoKXLvEG3/19qvpYndRN0IB6nqACCwbHBq+FTkMNXNs25fGllJgEYcHCNGjIDGNRIKDmlij+L9hAlQUXUOHV1o46inqCYZSBjLYsC9fv1a5A+eMWPGlitbsoVmy8Hl8I/1z8wGQx5Qy5/sjkEtWnRjGckXXF01vXsDutYC4v/jD71irnyPZs1CmzbN2o0QXYkODiEOjrXLPoYuzZ//kvKzkY9iiGD6cb5ZLz1XLt20aUJaYj0AnfPdy9fWtW3HTh1jYmIUI+nktyAVXvEgvkJKWLytuwdv83H5qNhDPPfFtGmYKMLyjJkERF/Ar9HXr0P/pUWNdJglmYYpREJ9fQWKaKkaHHQIzQYb3I3oG+K3uAlu8J9J4ZPsnZu3bpHwCvH3yY4bN6Ipv//IEayReDV/PuJOm65uOxfEd+8Sa9TAff0r1apno0dbnjtmzBhFJU4AKIC8Bw8ePG7cuB9++GHhwoVgGNBDgd0lk6Dq7Nn35Hg7fDjyBXkcWreoosN6pI1v0SgiVSkizFHIndBq23dsD+On4v2KzMJ/yiDCKxMT9nrx/fe07lGKjngQXfTPPx+G74WfTZtw+uzcaWBBdj6Vm5apyvk/eEBZTFFRUeeizlXVVYVXxXkkrYG+du1an+QcG7h1D5l/XXrtMTFJ+fLh+mkwYDYFCR38LFFqExiDE0wlSsTfacD4JKWWzbv3l+L9pByeWCvBvXi4Iib6Zti6Fc766SccD1Vm/V6Xr9tL26uXplc177YO7nVUl12cHjvDvVFahFSlNKVk4q/SngSNGNGJJWRf9/I66OICdo+bq+vZs2fhX6v0q3AL0NexiqQlxJ0KLnPGJQ2QSkaL9I+AfhgJRN4aAEAy9XHGeKYMVwZeccdkfGskqyyeS1HHdu1+oaQOZndFxsfHjx07luaUmFomFtMrHkv0GDYZHDbYnmv39fVt5+raxrVt7tu5666Tc0EGBpqoKnfLkodE42OPs188ffJkXDxdXPiQEIHI0AYN0lq7n3T5Yg6bJLMvgYh3v61XT7t0KZ1IpO9ipF08Omk6wbX3fKrA/gkWL9bwSBhHUnKMO6akhiqGKeQBfBbrE0OyiYmJPftgIMv5tPNWw1a5DXbZyCSw1bA3iX+kgNvJggUVV3vxIBbEcuU4qsfTwH6TifEJSw2TXhlI8jX2DHjd5MmID3/6iViPCp4qKIpm3I25C7e6nLZceufRmDFa8pGJVbzKoH/XECzmOT7/P9BvPno/7Q135FDkoXQtXqFCKJyVh8uTMhP++IN2wTRAPwvrW3MwmCvbVq82g6oXCTCqnJ15exbZQFMgdCkvlxdz/jQ94f1Kw0pzEIDt61u3bqWzWrdGb/2VKwqJpCter4ATx2jHWLtwYqXt3l0rDg5y0YmEG7LEHst+CjodALIWqp20xZUr4hugysFVqECl9DLETyx1JEFqzod7/i2arcYWgknI8CA+ciSydm39woWv9uyJPH36/ZXfPC+pyj6u0lhvMCxZuQS+cfzP43cbdq/Vr52imwJ2FLxJXY9oVqU9UqECUnFdvJhVGyEgZo4tbK9XrLh6NYplRnLExLJ+vXlRi9frNcyhSBUgWI5mPbv/cORh+Fybr9tY09ClEt4JEyZYOhLIZ1OhAi5q1Xgk7jxiOCLez8R373hGIRTz8CHxYYs0YbKiRnMhxyWBFMRkHhbAgoULM3Gxsn7FA8tZLmFPYp8wP5cjvLGryGnKFNzOlYrLkyMbbxj3BQ92b7S3N97GChUyvyAOHIih3soOZ59kzx/HKewEe/fuBdwP8Bpw55TJk0c1atS/SZOuXbqQx9ry6N+/v6xWJGOgilh68+QK9cxWEzD42sez4SYD7ieha5hZbm5u7dq1s0RXzMuIFHWNRmEA+rouGB4DDMWwsIQYHx807XLlolCJTJ+EOG3mz58/d66OCSyoPTyMAwdqZBs2Yi+mSDiPrSFw1pvEN8U0WIwEuF95/UzNdgqHu7s7Zby0b99+AyxPhlRCWmSl/PUX5icQJwx8Xtqmubji/v1bt4ylPVB/WrW+A7y21LS0vJ+xjx6JoQlrB+WLc8WLC0FwCEh7cKy2IrjPps4G62QlXaXGhsadTJ2GhA355vk3hTSF4F/dn3ZXrmPhOK5AgaUVKhBHcAc2TjYnW5jV+epwLqzA1vomJe6Uu8wZjYSa1QfLbOB/BPTDATOFwKvs3BJcCTSNuFImjYb8xNLamOjoaMpl/e23hxTRhVe1Gj1cOp2OomcwqtHjCwM4Tx6TddVAMNJkuYVp5iMNckOvqsPxWjCcpE0RrT45yyhYZI+zX1JKJ9Spw1NZVOvWPKsVMVi7n5R0LqWVpANmBzmqfGG3TWZSI6HW3LnVUnpZANyYHswXkBFAiRsQ3TqZeq4lCYRlmELWlODmJgvJAkqBTlb7qVohLhXpH0wlZ2dKzkzZQWDJwlzfNm2Cs2WLvpHiJ3oU+8hF6wKvKem7iR9KlsT153j76biA/PprZsZnUlJSv36YNOvsfG7wYK09A96wfTt87xVWktSiVwtVqCogNkBMMqdFzz/WP13z6PRpo2p7K2Qzjzxm3XhOchqxED7TLajvf6A/2SkVPgnx8ZuV6Vq8KGm+KJdSAUxaP+EWQtCyNvnGjRH0Hz2qjFdYjlB4csaIj08MywrV27nIQn+o4LIyXxnenDOeo79PnTpVivmomH3fvkjLBvdH7sfxobXq/1i0CCc2UbnTKVTMfp3Vbp54dyIXl0ua2GPZTxKo65pvG219e3drOQad9akFOEXEP2rUqNevU6TEABZQCHuJfkmGB7H7O/ea+ppfP/96cNhg2G7rns/ncllVMDCPg9oh151cbVzbtP6ytZOvk7g9y7QLSPNyzpw5rxYvxi2nbdss2QjjgoL4woVxAEycSOe6uGhZAQZ/61a0rE2jpydfvz51kK9Xz3jihGKbw54Nw0qsbePYLvibZfeohPeMUoLjoUNGQPzwCu/H67DuE17F+wkrNSF79FXcvSulCZMVNYpH+fKctJwIdlviWmZMFKYB2hHo6zc0oEJD6TExfCJqzwluad9PgwEMIeyYklCaDKDXqKF/9zaOTBfh7t3MLIhkSORzCjivqvBs9Gh7nrtZYWrdOthCIiIijEYj7GG3b9++cOHCnj17YPDfkGxjmQJVSUlDm1/DCkLVk5MVWpXQIGY68u6I2ObMmTORa3XdOst2CHh1XI9FHR13YfnN4MFm4pGw/v2JWgp1Z16mohcjfaU+ffowuGOuiilYkGO+hlRgKKxfv9u5crkx0ltjuLGlsSXNuKp6ZdAv0zUzu2BCQwlykeUZHBwsnkWUx506oaIc2QZSq4DSPK6oyvR3vYP6SgE5VMGOpVtdyBmC1Oy3jLdk95N8nPR8rc53QeAbNRIFg7+Z9oRCB5U2TFD1+CN7u21Tth33FrwDTAFSWJ+SIRYXRHnkE8InKOT0M3rchw0bUiUVrkJVq/JMPny/YT9lYFtOH+khEnfK/U2DBmGfhw9XM/VaqXbBPwX6SY9M5o9YpF9EMXZ4PXxwBq1+0jaJAwosIo0mntaWwoVTvGZg8lFMyd/fnwhbDclaMZbH59znUoI+2xfeDkznNm2uVy7n5I+F1F3He0ld1DBLsmfnaPDHgeVmn7Nf2plr1wQWFVOzuj+1n59g7X6Gh4fTNUrzBqmmCCDnOWdnGW0RJV5u2WJeloOEIFLnWP/WKhWhsVUrzMnZs0fs5/nzxhw51IoqwtIwRSoTlOPMxoPESQ+fRydIh7bZ/bK7alzFnaJxY57J7aVaQIiqaHqXLlLiRAAhObmcWL3K5YT3KVkMLGA+Kt8SKn/P5PjcuHEjfHWVKr8S+3CaB/GE/lqrFpIcLK3QxJiKpHHEM9z7lr9ent555PgQ14r9V4Ot9fPUqfeqOsdwReWr/gf6zQdVPkn1ye256bAfYLYfn5Lt93bLFgxzW2GsT9m0WNY+eSYUEMvff8N/TV+ZE2OOH8eiwK5dTXYusk01mKq027gbTGtYVLQmsw3ao0cPGGpPnz6Vjv4//lAQ5b0efR2BF9/A2oVTksb06Smgn/LbTp3CMpQa+hqi7LO1fpKQSrWCN0XiWP3mzeQbMyUvgtYQPx2kRpGfy/9QeJiBQQz2NJUcKPrenNXOTaZgsr7retfemt59tH3g705qpyfCE6nvs0uXLi9evIDViiBjtAU+S+9GKDx+TIxAT3v0EDVKHz6MKVdOK3IjytsUBFi+CePiDSxVynjuXKrhZDIU0RSB/93Q36A+yzzHVMIL20NMTIzt7h02YMSgGl9NvJ96xhQeeeCAcq5L6qJGOiZO1LLiTi0Vh1SuzBPX8vz5uiOR+Exzc7kD4wIVUlETX9GFwKNPA/Pv2oXfW7Ginak4gP5JS1tvh+6VtTbFlKH1jl3EvTztiASbCAANPyqoigsOFlq3DlQ5FVLdQ0/u9GlwG6VbjilZxKNXr14y7k74tTPLAF70EJFWjh3toAXR/kR6fsbQASNB7sBLLmB4+PCh0Wjq0EFDE8zFRR4AeTlnzkLGeb9oyaLOJnS0l9GUIW+0ZZ2VOR/X2VkxHxeMJZLsAPS1YcMGSmYLD09gFZvco0fBluTCt24Z+5U/6KgKxpDaUPSHNQlAKqd+2n7wfopuiux+kmMy8uBB28/I6OVF0Awsz5n+v+Kl72pOTlAyoW1vrrAIE2r5/fXvsueuadAAb/jKlXSlPbp3D86TB4mPfXxa861RHOr1UttDSCTuTD0WdWa9s2vXNJ07Y8LM+PGfGPRHX72qq1wZXlNyPyIjiRM9JMRcX3FNuEaldD21GMqu4ZU/JJtKv3ChtM1RjITt8mUUzSxTBhecRo1S8VNT3fOUKVNoAmp691bs4V0Bky7AAEv6kJTmhdMmCAaY7ttvO/thXVy2id+Lzv6WLTVM10Ir9tNOZ7+Fx82cckk1dTbuJw0PMecWJjKFpjeVLs1XriybPpUq8Szyqfbywr8P06KfqBHfyMaFEx+AqYuZaDI0VCCHjkzY0TJMIW3k5c8/401ITbsEBzENVtpWCbqxSLcITndz0xCp9/37Quoc1NlIOsdCu8/HjYtKivru+Xe0ldN+Qeo0RIxz9y66UIupvEMLFTGlxXyX5hOHxQ999i26+vrq7RzzXJkyXVu0gLPyeuWl1ErxOBR5CLraVmibrnl0T8C0W9Xdwt9889xaP8ePD1fl9M8Wmh0wIW/6j6efHbsidlnm7aV5X0igHjCQeEoEQxvPhg5NA/Sz+KkQHKyM/BjlsL5GDTpl7do3lvoyNvo5RIvJW9/pcNxX56tLQ2DdunWTrFCvpbWM0gM2WnQXcZ9bu3CY1cSPKw4OChqSkEozYzOML0futNFPcnBuGnMEVq6tW80ThpzWOlZ1YBvx09HzKS76nTSd0juIL0RdcOadSZ72t1e/7Yncs29em6N1VfcWf/sy8aXRZGRRs9OED6g6sIOmgyhzplarARuJnOUfkgu4TZ07Z2oj5DieVUcZGjdOssK6YK1NQa3WTZuGDlcWnQfAIf7rmOEYJXLAKZRQfuvWrdT+aSzhXc3SydJAqIIuH5eP4kgYNLx8mfIckuKsuhWlRY3mZNwzWBBSogQHKJ/cQmD1Afr3EXxojV73Zp211ja83UCJj6L8nLL7vFMnkY7N9j3Eotv8TEFpAPLWa8C2ztCC+OSJuTh4Qu09Ujdw2gFfFvLiJSWwWQuqkuLjXy1eTEnzmhIl7v7pmavkA5UvPkSvKC9Zm5Qae+zYMWkjJ0+ehD/CZIQHhLvL4zwNmqZKNSTDT1+7tmU/KUSwY8cONrrNJa0VK8p3nbBt2zoyxr0+d9G6LqYpFhwX3C+sn6JgjYFFU2EBsXbVWq12xYoVKHzDSjYfPMCx2rKlkUmd7KQq6mRzN27UqGekgwugv38191pBX+CXGjCV393oDu9LcCXAbBbvZ+K7dxyMWkfHxGRdHhvPSDcdswjUlSuV58rjrftyY758nIwjxUYjAAJYNYQD5Z2aM+7Y7oA1iDx/7do1Yi6iAX9uwxTK7Xyd+Nr2EBKJO6ViLJR7QFJfVNwM+5QpOd3r04B+XcWK+L3ZsgEUFl3gBND37dtHS1BtHhOlBmgGwCJQJrQUvF8wNJvw+LHYJiVb9+nTh7wbTZvio4dX6Re9ePGC8n+2MyY9Ln9+k5Jq4Fo9Eqh3e9rNLjd/u3Zubdrczp0bJvUewx584qerEEMxyUgVLsyJ6i/k5LbH2W/ZKzCbcVhVToP/fgGr9vb09KR8J6q7m0UW4+bNFmmHBiwJxZHFLTh9DEadk9rpqvGqjY4lhIdT/xMYgUefPloWOLUqQS2GKY4efSdWGJCMt8jvLB7kg+gzChcEsPHcxlykvFApWxFRI1DhE3fkCOrBD6xbXV+dHPx/vv4z8UMivJLxXENfwzfWF1ouV/QRJhc0mZp54HvlSlTDhkgxDIuknWP+JPODNBzaMBeXS0qIRPkL2dkNpb9bnqvftYurUsWwLZV2MmVhqba1LlSIj41VttDKlsVHUzmoDnzS0+j5H+hnIyzqotTGsnPx8jRg1ewXmi9S3BIsJzKsXz8bExjwmbluzJq7NzQUl6HcuT+wwNzMmS8Yw91rOxeFX3RYBt6cR27dvtq+0p0brOcUO2cXhryHDFHQB4lNioU5D4OP4K/l0a2bVkwopFP27t1L+bjxSfF5uDzw1S8SXljtp9FodimlrhUzsHkL6+8Lnk8T8WN4Md6Yn0N3oLTcx3D6NOfiAq/WBvGWt1vg0uAsQBXRSeiwjDcYaPGKN6bIdMNqQp6S06wpgs5FuCKw01Ba8NixY8XIaeLLl0SlH8MQRkY2QqNR06EDQtUKFRKePcvY5mo8f55jqUFcgQLGQ4foj2T+zXgx4wOqke+WFYaKJbycfZ7pzprORNyJgL53b9tcVR8sihrpKFmSEwMrYEBSPi0JydmmIIBFvK6+rkhKqzx9Hj2ip0nJCWneRqLXdMquPqhqgFjKYEjvgujtHZ07N8s0LaIOyZ5TuounHdthxS3I4/ZcbtXfj7lfTlcOXjMMqmLu3SMuPLJDCKf2f4RZUqq/21ARs7RNGh4wsFOtJyxnZv369fA+10Us6pjlflLan8hjxwDxv3NXYJsxR96nmxXBDxwwAOKHV1k/dzIXaccBDaBxsMYfxqD49PaI7YqCNVoihLVJsA1HcHAwaRjTgF+0yMAyfCaTA1gK9+F1QMvrV1RlrgxpQaXqojOsAlcB0xQNu8Tn/p4ZacZmzeyamzodV6nSttb4AIoFli5bIfTkSWO6NtffX/+OoIfLdT36urlJ5h6WJdxTYWLvnZgT/I32G3tWDyLupPocs7HUvbv0xmpYQEP3/fefDPTHEoemoyPMIFzEsmcn6H/q1Cl4alOnIkqbrJtM0fUQAR3/G/cMxeKxR06BpkCxzblz50prWLdujQDED6+yr6NobYcOHW4SX+SuXQqJkczhLWZc2OPm50qVgs0DjJMCIRhJdqx6Dsw84maVajPTWfY4+y17tXu3ERD/nj1pjKWjR48iRQ8jECcDYFi3bgGOjob69RWd3LAO486eI8DhfEXRw5XGs6akmg0btm+PIBLw69dtuc8pTFEEdlETUtaQtreualUFEBIbS5Rifa4h7ld51CpQONhS8pYSlgYMGBAf/vznUdB3lRTf0wHvKfuALIFJ1TdgdLfh+cwD359/flmmzDrowOzZs+0c8z+zEt4y68oMChtk2WAboY1YXKrgFaxSxRzPr1hRN3Om0dtbnBHFl02C/3h4vLNsk6SpixfXjHo2isIm/4F+FqaJw/rXyrrK6Vq8DhkPUbFXSsLA8eOYm9G9uy3Qz6oGeRcXWz5fRqEQLwhi8v2ePZF2Lgq7DbuRiY8rKWXgWbcOh+aGDSnVSBcuRLGCfWX528+4z+B0aQ2N9GjRAgNtFKSmz3t6ekL7K1asuBdzT7ECT9pP4eJFHLhlyij4aN3cfHLkGNapU5qI35yXxagVinPFgwRUUxeCgtSFCmHjDg6aAQOkhIlUKzPrxSxCm7NfzBYDl8RnEjZwoKyfmzejhPv3ydtePR61smdfnE0CnDKevhdM4gdwcMY2QtrLuUKF4oKDM7W58jyVicOWSQTwBFyuRWMth06no4CPyFcolvDa2U+A+0TciYVcsD3nyJEQloaupLSoURpKzpWL27nTIE3SLaop+jThqe3WrkZdxRQgde77wn3FHlLmmKZzZ/sXrxkz0K4u7njntqqowdMzXQviX3+9oayezz7TXO35gyzb257l1czjdvSozLwpocW0e0e149yXc98lvktv1Eg3bhxFfnQVK0ZdumS+e9FXs6mzOYRmU1U7SUXM0jY1Gg0lAHiz7YQVRxjIJnzw4IGnp1E1awyigWc/2Dk+nzCxts6dOxusm1Lwrz6M8LfQ8UK5udyAbs3VAlYEawBGI0RLy7XG3IgJe/bsAVTHxnyvYsX2tWmDLKLDh6tFuD969LNbt4zkPp+wEFNjB2oGio3M0c+R0dSGT5iAhu78+XbOTaOHR9utuOD89ODbjG2uE8InUIbJDeEGlfCi1ZG6nsEUGOj9efbsQTha7gh37Hk6RNxJ9TlmT1OuXJgjlOyIMbK9DMxgikh/AtBvYjlFL6ZNA6APOFiE/urhw6ne41DIIRi9cI2ihgzfqFGz3Xh7R2vNdczPnj1zc3ODD7+yGYqhfpJBO7Jr12C2X1j2sAqPDFe3om/Z4+Zv5+p6O3du3bfmBz1YOxj3mimTSIm8Zk1emlAjZrSLzv6/I/5uZGy08vVK2RqY4fsZFBSEQH/YMBJ/7dK5863SpZEY8NQpqz4IwdRoD8aLVOcqjpsUCr/avvAIJjPq1aA/EQyuWpV2lourK4lqmcQ48OvlyjbVmjVrUPG633yVF0qg9r01SSEUs3Yt6qAtntvB1IF29nHcUOmKQQf8ZXz4ePpAg73Oqs9uOecP0ekyC3zBmMyZ817btq7t27fnOM6OVZnr8OWXbdq2yXk/pyKjLpiX0MORz0ZaPnfko2OlU2AzicnIfIMGbW5g6ebwPbtZ6pTCXrx8+WvmXHu27s062fr2fxr0RyRGYGCUz5uuybbDsAPOaq9pL57y/izqy5o6drSV6+nhQU/LVn4Ci8FFs6LbZs2MTFEi2s5FlioNcqhzoMloPCStOr0oYZjx84tleYHK9cEUQj1tPK3YvWrVcIZfuiSIg8PLywvn3ty5a96sgRPBprTRT/1vv6Gzql8/y5YDPT0HN2qEC/HQoWkifsyvNQmNeCQVGaYdBniXKqTV+fNzDO7AYipCf5j2pD/gxDltfbtVbCHp/XsqnI2+fVvWz+DgYJI4ecxixxv1G7MFZWsxCBPyYK2RTQzAvhzbNWP9/NK7EermzlUzfhPYaLNgcxUE7cSJtChcnjuEUhuJDBgOCqGIFotYwmvnmAeoTd7QsJ9Rhy5scNpMdrKiRubxNQLuF5nLxSRdayrismNA2ADkNtF0V15YWUW46Lezp8H4+KQ2bZBWqLFqH//9TDsXxKiopOHDn9HyO23ai6gQhWC9PcurbgZWIoZPnSrt0m+vfiMXr5nAUVtqV8QuMlPTDhodOsSXLUv1tS9mzEiKwi2Qi+NgVlLtYyVdpZQi5neJ0jZJMxjAEP1KZZRDhw6F9716aVTNdtumg7Qcn0ROZ0MB4MCBAxTvBszqyW+XtmApWCM8eYLzOk8eQa+3c9MCo4K4xeho1GiICPc5LlmVludDszmUuoY356jhqJSqgQLu8IbapPwTca1Ic256G70dQlW5/FQPXJXdq2neRjD/uj/tDh0ry5f1Wb/Q2t4xbjUCo6+u17dzzBNxJ9Xn4Jq8di223KRJqm2IkTLpGZHrxwb9UVeuYAcKFEhIFnuRQv9x9erBs6uxs5q0ysJ4+zb860ydXMTrddl4mSXSIBP/woUL7ekngDAK5y4vX15dsKBsUPkL/kjqoM5luypadPPPpZrgZK8B+QQdLpanJcLdXTmt6873fadOVFW8U0BaV+aidekX1m/F6xVgA3MmLmOgH4xe4imigu/TLOvd2Ly5jWfkZfRyUqNQafamB5lovRZWOVuDMzIyIHfBaqqT8OG+fe1isPHxEYjYfs0Sc4DdmttIrcaM+ZYtu+Zosj9bqKPU2BMPSlgtdwwJ34r45tjslko6QHaceHfiMzUa9o73CqjcNm/fbsgM8H3zJhH65OTETZ48VVSyt31Q5LPuuLolbzgkxCgQJ/rH+qMTU1Mclno5JhwwAJ1ZAweim2T/foBPlCVeCKu0VCf79nRwwEhLZKScGIC2tkOHIr2jvTEMwtX4D/SbD9Itl2ZZpXlf1hvWwyk9ND1kK5fQpo2NhYYqVqUCkAqgnyVOROzYAaeUKoW5NFptvJ2LrNFkJMSP9E+CmSWdqKx1uhRNwZcvE0n+XbFNSmH/26DMaUC5uTB7xcFBaZRTp04dGDaQeCFs9FMqRCo9goKCAF5AO0MaNQodPNjODUZcpw6PxTWX+/xz4f59APowSURf0f3RPRpz6KcvyBe8GJWKW9PMPyMh2k8VjGOsRCtXrqSK2Dp/1EHfw+Ce5LmUdSacQe2wIUPStRHqoQOMyVy/aVMWbq5wezknp1ljcBgMN6V0adu2bSia+8cfH1KX8Nq/YRNx5/4OqMAafeuWPf2UFjVa1gmISbp2Xrg+Xp9bnRuNBMMx+eB3dycOUzFLx842w8ISihfE2PCYEqvsWRB5Po7Iv/PmBeslMiVSn5rUxZ77SVlthi9SsgRvRN+AHQ7GxLn352ClbmxoTNMZQPDN6Ju22goMpL0B8VPNmjFMmofgPqW0wWtlXeVr0dekRczSfvr4+ICV2759e6qbpKwAMHF9fQXY3hxzBebh8kI7Uipe2+Nz8eLFopGsnCs4DIP4JXeVXN1V9f7sWWkLloI1hq1b8dJatUrXppWUlHTixIk2bb5kIsGDRbgv7ee+LlhPUia4pIwFmKjK5+gx6SWOZWbyhQt/sCIYbPncx+rGYibhqtyWNFb2j8/3Se9pDNQ9m/dJbizhlTUSKoQWCED78Pi3zexsUyTufCA8wB2nXTvsYTJxu3k2MeFhrkgRk33asZkB/Qbmr3m1aJG8nwz6by1dGp5dram1al8tpL2VnOn0AwbWtH36jNKOopA7bHDEV+Hv729nP728vNwY5c5ZZ2fjgQPS7m03YIJZc01zu9z8bm63c+em3B6RQYGY9FTVPS2L18MTwte9WUcCQeaqU3VBeMpNDE1ID0v8gTlbk685TDtspWElbHbWcm4Vn/uECRPI1t2wejWxTUSx4mZlZ5FJaMg3xP1CO/zQIbN4XJMmxmfPEmxc/shKe+FjlT7zDQ21lz776FHMqMzlFHxOVfFpslqo5bFx49sGDdBF9eOPh2RpXXQ8CX3S1rVt63atHQMcO5o6BvwyHofQggU2ehuyfXnLHeYbW27nUNtVrbafu4cHXkWrVkYq/7MkvLY86HGU2FFiwjSrjgOSn78bc1fm5icDKZXaI8fd3o4R8sJYba5qpNqPNBItf39/7tyH5Eg+WCbsPA7ewDIiI3f5vw76q+qqwp0TaVPtWbxW6JHPfpA2JTcLMJAMQSqAfiZkoxs50pbzjwkevZw7Nz4+iWU5quGN/YtsRb4icYnSr7B/I5Ftp04y1U+UPlWpFU35kbqR0MJv+t9SQOTKlXy9erpVCIkoOE7RMalRPnr0aBetizWCs5SxSqzYN28qIv5hAwf6ggmbLVvso0d2LtzTtd/Dl1Y8pwoqWVTKiUTQ/1xVx9JezH3yIP9jdWq5n6QkffXqMv4Zy5RB2EgA5d+7d8+1nSusMs3ONVOcGPF6PZoZDg6vly+P9vaWZmlbdcp6eKhZNatu3rwsz501HjrU8LAj2mCTKot1AgT0e/bsCYNBWsJr/4ZNxJ1jZqXIqdjTTypq5CpVkhXMSVdz+699pg6TE2AvlG2B2n798GZOmZKBxcvjQGh2VRAMlM1rQmzfgTNn3hcuzLNaOh3pZMMKzjk4WNbk2bUH8jxaRI6ORFr3MvElCYTPfjHbPEg/JO2K2FVKW4r2qp6anvcEBSVmMBppZqlz5tT9+KMAozE13B/9bDT8RRL9Nxcxr179RtoOcftu3rzZaDQS/c7t27enT9cxDjFNt6fdoLXtEdvtfO5UTSSrExCP+Wfmw3+b9Wi2/K82KE6yapW0BUvBGu033+DznTEjA5vWqlVerVoNgVfFfvbbjgSFU672krWzy4AcDxU5ZIIiRmapIJHta1cL6gJqBHBnDswzK16dP5+xzfVZwjOXIMzYbPd3diMvF+NboF+ANuF+VipmN0An4s7f9b8Lfn7mMhh/udwhMVrqbQKpzIP+SCapqylZ0hqBwZqr85FDuX1rz0qOYvyWY1EXw759gabAQhwqG/y470eUnfr223T1kxRs+jZtGjRkiLR7VA01TTfNHjf/AuanE3N76BilQ2vE+bdxHh5mHwRn4tYb1n+p+ZJmJUZN+Xz93SvtaKkyfT1SnO/+sf7bIraNez6uvqG++En6yc/lb8Q3qsZXs3TJWfaNincHDBgQzkhyhHbtbDyjxbrF0lxZLy9zKUK5clp//1jFa6eCqByqgLNVe6bruY8ahTHSWiqPNx4nFVvevz8SkM/nn28lPK0TdHX4OuQbokYuChfrHqwL/63/Xf35uvlw0yjXKKxvX1vOnf79Qx1UU/b0QmZetaqSugq0kzHgO2lSOGkUvn//ntTH/f1tqYX6+fmhRHT71tn9sl92SRFikh2UhjT/1XxlN3/qg6p4O2rdYGlaUmEO9KetCt0immLFdJUrg4F36FAk/rGtOYu7Kl/VRgbH/znQ7ypgHeGFqAv2L1601H6t/Vo8JebhQ1yGrMtBm5Jlg3QzbWUREBNz2JAhWi3SDJcurU3XItuAx5K4WnwtaYwe9l3ZiVTTLXV6icePuh/Rx6ZNoWwjYhlN/fpBQSbKoJEOjufPnyPfX99e5E1X5PkyuxNu3EDwV6yYMuIfNgzeh0+dapsMR9Zm6IjBFVHbV/X9vWGyW3HQeDB/KMZw6h91uFMkpThMmo6lLVMmScJiKa/lYpQmR44coUhirfm1xGlj2R9DMmu+2dvq7AzIOGzgQLDi9KtXGz09hSdPUjwr16+rmfdFWpaXhZurn+CXTZ0tR6DD4zwqbblyscneL7rVYMNIS3jt37CJuLPKaXMkyt5+sqJGHPnJZZ1wHDcelybp2n/tSNzBITJeqk/xTQrBwVgU6+Agq+Ww/37OKzcfeaBzBVsrRxME0w8/6BhHpbp796dv3jCPb2KihikSaCtUyBgA4hs2xFzb06fhlB5Pe8B1NTM2I9ks8XiX+G7uy7m5udxEZwFYBDClmH7NsWxdnKHNmsEUu2W8BbujNbgv27OdnDgSzUk2ac6QsvKFCxfgzUAYvTqBmD2OHDFQYuiAMHuBL4yuduywzHndbdhdbwKmbXz797cA9y01fS0Fa3jGFGQ4ciQLNy2CYnkDUJHj6upp8jiMyUA6UO5Gd1Igjthur8GzTL+MeA/xK0qWNFMSZ7SfV2b0LngfnzFASVkPaS5sGVuRKubtbJCIOztrOlPVjaZdO4Uw1M6dFDpLio39SKAf1l4dq1CUyjOlajDBBJi+/tj6MFQO9uhhjt9SAmfhwhTTg3UAZ82IZvCZs6njRWn2U6/Xj2JJaHPq1ZMSWX6hQSqnA8YDabv527W7R1mFqSuCiADKhXeBZ7TPsK+vtm9eFiijWdnV1HV/5P73Se9t0/jwJt7D6DFPN6+btlsprlRKBECdXboIKI6lW7duAe6/efYs8UyIgVnLZ3HCcMJJ7SQL7z9+LDRpYiRt0IsX5ekoAE4KFkSvwfzcY4np1f7n/vzs9dIqdMX99KMCf+CpU++pUGr27BCSZPb19RWzQLcYtgDKz6HOUW1ONUzl2rSQ2iTVPBhLtjaOYsWILb12/1Oqs5UoERpaU1T5tD1+qlfHSOmNG5h3TbShm1is3tpBJYI1ZtRocb+ytYwAvPb3pyiom4abX+IyIyHL8PCE7I7q7NlCfSs1NO8FRYoMH4DOmuXLzZnSREMM69J/oJ8hoWfIA7AjYof9i9dsHapaTtJNEk8BXCVl21RcI0gzXP/777Z8tCxLwdi06bVr0fDMmjc3pmuRbazBWHATTRPpaFuyZInsROIyo1ErO1brV0MLvTUp7MU884irixb19haY9c9LB0dMTAyqfnRoZ4OAxbzCrlghUz6XIX74S0J4OM/q1aKuXElz4daOx6DegeY5iGXMy+glDcUQ7oHlMoILkBaHEfQ3Maq710uX2rifRGkC0Icc5N8Fovunu7a74sSI3L8fuRG6dQOsD4hfSQYAqXX4unU1nTpx7AOajh2lO00Wgv5V+lXwfa7BLYxNmpAFQrLBYoGytITX/g1b6+meF0nPVPr3XLr6iWENBwfAmMQoGiKEwHYoTdJN17XD0o/EHVwhkbhDv3QpXmbLlhkGf7rZs79SrSIWUbVasEg/E9q31zCBZPVvv70Sw2avWI0Klzu3ZcTWzl2QajBezJ5NJTFgNmvjtdZSm0hpm9gk1+jXwHbFUQa/k5N++fJbBm974L54mIuYi3OPHgnJho1Ao51c/itXriQF7mrVcMqr49RUV6qoKqWc4jJ2rCWrHeChIl5FkFC/k1tkZOT7M2dwM3Zzk7sqJYI1iW/f4q13crKhn5qx577OgJZM/cMqbbKurfSA8Qn/7c/35VkSbYLJ3tQmSoTbaEDldeH8eY5ieosWZaCfSe/fw7pxoKEqRygis7m6uWIL0D7FIrRz51C6i/1pclSfE9K8MSnEKRfJ1KhhA5FnHvQT3TtgtaR45RRW2FBwHdvsSjQpFL8ldQiualUxqbXuefT7tu/ePi4uLr39vH//foc2KFjunqzUAXagE+fkqHYMFULTdPMvZmFMrYuLrGwD5mYRNaaNFeRSNGEa8A0W6xaHJ4SniuRYp/GR3TRfwfdP/Z9UYSxdBGyMpRfff48kExLCblkRIKwYVO1Tmist+7qoqKR+/cKoDGbr1hT9rPj4JMIPPXs+ff711/gEp02z/7k/Gz78oKqBo0MI2G4yBAKYh8jQZs16AR8mLqZVLMVgkW4RVeXRtbfr2Y7ikGaijthYzskJBgZVMVkesX5+5uRPsBKX6lW5/Er/PYyaKsuVHacdN103Xfrzy8tfZD8zXsyoqa/p/s5dEOJJ0J1SMCieOWzYMBtXTd7DokeLbvH7FW+XFZrmqKSo3BzKAj4WHtt288PRVtNWWgvXpQs6ZDdseBt1/jwg/lCVQ5HsD+AvYqCG/NRDtEP+A/14/PDiB7gdi18ttn/xIjNrlm5WSgIiS/rUWTj8UoF+lj1psNAVT7VYsIgBWKV79kSKebf2L7JL9EsA8YtqtWb1Ckainyq82wvV6Q8fVuAFOmTAIqRmmmbJ4SUNZaHAz/GVaKB/8YVGNjiIJSNbQLYFrxbY6Ke2b1+0eZJ3PkvET20SkDI0bpzGvvXTTziNnZwMe/aIeiICLr3CBO0Ems8TtRPhV2mGaCpfUe7cMspti+QLvhNjEyLldh/BhzYDe1gywHqJ9vaO2LULFkRNz56A9Yl8I8UAgAUotQc0C0F/F00XEi2GRTCM5b3Ahb/dupVYHai6SyzhtX/D1vTq1WG9ylrlhu1+aocNQ1zeqBE8ogHaAaRzLJKFp/faW2paSok7eKLeY+SSGbufxjNnnqhyV3a6BJfXo0cqKYDLl43lynEkK3v2bEoSQvSNG5h+5+CAmZQZBUAweqHnZwfXI0rpo++O2u6np9GzPl+fxlC9oBqHGmEHbp7ZLIX7AzUDbcN9cfOmSq9mzTQixQ4VftAIuXnzZqNGvEg4CKdU0qGH7Ha0vcWsxLCxRJLRft54Pj+Xv9qP1URKwXhYYZjmg3whkgjWvD992jx4srQQDT7cRoNMeQsGqzSurpZNASpCHqGQnL75VPo69hYxU0CsOFdcHN5UkKDOlUvqE7WzkxFEot+gwSb9JiLvhzfUArGKLdcvJ144dYECSfahXjjILNnb1EGdO7cQGqocdt60CTe18uWtgfLMgH4wZjRMWPDdkSOKra19g0z5hbnCVx5fcXV17dixo5bxwBt27QLEL+XZHPsj2pZVf68KxkwG+vn34MHI4Onq6u7urtfraQckFfY03fwBjNPpRTLPm/SoxdeieQpW2UzdTFHgWdYUOfvhwVpWSVm7e6kWAb7eCeMJ5QluNJoZJnx9ZW3K4oEAfD0NngrPKOnD7NkvaMsCIE7ODnjDhPa0r14lRjHyK65cOTufO1jvHJOTmz0eV9Ty5XURESlKlAUK4Grz7bfPqZ+XL18m0UAjc40V4zD0l1Odc5X3KnLDSe8naYbE3L2reCvesGp1LdMI9/MTKNn9r8AdVCFm/4+L1mXb7hes0Dn5e/V6kn0gC8TygL+jjFfXFvlD80fEvuYYTbNMwlw8uphw416lX2XbzQ8HzAv4pC7eXKu5e3cElRkg9nj+3LNCT8wTcbopZhpT6IlG9X+g/8PqN6utyZ5bO77RfgOn/Kr/VTrBcFSVKmVjmeBr10Yv/pkztpoWBNLTWTQfjewffniRmUWW/Ha3LdyQqNOmUq9Z88ayzRvCDcym5culqo9kLDdbu/4BZ7VvLwf9VCuc815OaYqUQri/TBl06THKuXPnzhEXrxTxp2wGLCBubTP4kFyDC5a9YSP60kTlcDBnv9J+RS6BP/R/WA5igv7kK9JVq5bm/aQb2L9/f3P6L4uR2cmHbdmm4Odn9PQEs4evUsXAdIs+BujXmrQUSiYhLVi5iZkUN6dZs+hhde7cWSzhtXMsCb6+YGItGpSNFD3Tfe1BQVzx4qjLtnsopalcE65l+NovGy+LxB1GJpGBQq2ptWHS1yZskIULn1dVyJcnFBpbuNDM5rFhgyFPHtyfatXi79xJYbmFVVvLxjPc28wAICE4+HG+bOUuOcjqVm20CXbsGv0ayjzBfehOXkfOUYT7hC3svHAsYmbZO999Z4anarWaeD9grz1/3kg6smScfkgmkZz/yl7aSiqMGTx4MP16XbhehCuS80FO13aubm5uj6h0JzGRVrzEiFR86lLBGhrA2okTsxb0gxmPWXChTg+cVXzZsoqtkXm5cJDqxQ/20pWSyT1DN8MyN5evU0fQpc/QNTZtSiq86PvUzSXc42H0kOqHiPFYRftTOYE4uT5H07279bizkRLzInbuzHLQT84dY5Mmik0FxgVSPhvlnHzzzTfkebFsKiAgAG1Ut7Y57+a0J/fMsp+wI/dr2pScO7Aw9preq+S2kqMejrLxjMjND6+0CEQrwbIN+g21+drrDOvSHJ9apsWuLV3a/vspWwQGhQ0S8Z94PB83DpNJZCrUqeG+uGLYmEdbt76llJu+fcNOnHgHdidMy5s3o835jWyzNp4+bc9zp9iO0K5dXFxSgwYGJtCOJWdBQXGffaYh6kkqlZfuv6cY0+hF48XSXGl43bRpk5RnzLyUDR6MUSkrGW4kLGP48086pV07/K6lS/V/6/8G63ecTu7phyVO9jPzxUyS9ax0ZBCcu3LlG/EZLVq0iFjLles/V6yA/1b5tQrRcRoZTfN7K3lof735i9ITbLv5SYsX5n5KokFkYu7cHDwavR7t83kz8d4OAYhasybh/lAhFNY6J7WTVJXv/y7oPxx5WIZj0hy7RMRLQkWiZxefUNGitvJHGegRHjxIg32FLd9j+wXCY1u79k2GF1mO41wZybHBYJCduHDhK2j8xx8VzE3OxNG+Ys7HZtstabMvLfodm5Za2eAYNRqVzwt4FYhIjLDWT+H+fTMyY1b7YOZcAdwvRfwpYV+G6a2FfSP37yfUrk8OyIp1LYR+CqgLiIylioM46vx5QPzwmub9vHjx4qBBgy4lc2NfEi7ZqXyZ4ZB35tskSUiq60gxk7ZuxQCoSjWCOXFhE01vP6ke13uIGyl6pklmZ9mmYevWEzVVOXBcy4VCMnDtRNzR4kENgoxchQqZvJ+aHj2gnY2Dd1Gy+7FjhjFjtOTh6d9fq9GkavMp+7CxWTNrTlD7n3vv7eizqR1QMSYpxv77Gep7a+J0R0csP1Y5cA6yzdv+az9+3Eg7+pYtZm//8OHDYYSMGDFiwAANc7ylgFTP9yhK2NTY1M5+wsoDKApa8/Pzg43qc+5zzNZY7iqK2pi9ZXXqoJcutfzFB4lgjZExSBr27MnaeURk/F/xXZj96Cgo0XcTUVttdzP5SZrHfeE+tAWbK3F9pqC0kBDexQWXtcmT7e9n7OPHogqvtEK0oLpgC00LUUcJpydL5HhuXyUr7nrJ9TmW3odUmxET/0L/SFq0Reka8ylpnF5elu3A2vKF4QsigKbPE877+eefLZuiaNKkHyaRNOTVqKsZ6Kd7pUqDGzce3LNnW8kxbNiwjRs3Pnz4MD71HBfd/JpTpyi350NSUmbWebAZuJw5sZx93bp03U+1oJ6mm0b57mAjSWU9ou/e5RgTSFxgoHlnT13cbwPuW/bz4sUoZ2eeFkZ4XbQoJUJOZXjaMWPsCmyyEqbIffvQrguMo2SeTZvelimDK23nziYwBqTXTvmoM1OXQRITjigfTp9/zTI8wydPVsqQSyJubmOyM37tWj2jJ+LTtYb4xPjQGFON+plYHKif5Nro3bu3YMHMC3/pzaRInM8508ikhCtrREOaeA0CGK6A9tYNG25+QjuuGlfpuSTrREn8jRoh6N9RdgTCJIb7keWFQ5aX88bz/4H+D0Ri2tjQ2P7JRsm1fxlShOITIyLQkZM/v9WFxmikKJ6QpjIEKxrr2MAHHtvx4+8yvMhSdGw0y1WVnQi2O6k2KLbprEaL1k/wQyTk6orb7YYNXNGiP6jGwlnjx8s9VSMnIbtWg7MNbPTTwOgvNO3b07nEkezp6ZneAq/3p04ReNVbbADk9gBEftV49SOlzcDRmm+NVaSvl/5rQf9w7XBFVcWoixd5Z+cDxYqNaNr04u7d6WoTBi2ZrIYjR0jR80rUlQz0s8QttMqKeTvoly2TZsFm4NoDeZ9CTzAl5q+OKq5UKePhw5m8nwZWQ6/p0OG777AEKkcOjm1y6iVL5Gqab9aswclesGC8VpvJ575SvxI37Cequysnpet+6lhBy5GJzcrz5Y8bjmfm2hcswC0wXz6zpqaHhwfg/r173QGHAGzw9jaKbQKkyMHlAFD7KvGVnf2cPn06lgfsXZlXjdGnJoFNSAXs+vXrKV46loEWuWePrB2zYI1pGObEAyhnWlFZOI+I0WKnYSeJGwjXrytUWvveccbkWJXPu3v2tDlJNwldSJpeCn7z48fJujAet7d4nRTBpOX+RpORWJXJNfNEMNMDkO6hpkQJe9A5epevXqL6nAfa27Ymvl6vY37oyEOHsnCts03Y8NPLn6Bj5XXlIxIjzOnsvr6KWm96vb5Xr14kRLPgFWYt1zPUs7/mJOUpMzogdf78D0+4l91Wttb3tTp17iSifxixc+fOhd3qGWNCE938LxjVHsC4zK/z744epYxTEaPb3ybYmYPCBkllPRLj4yh1Slu+fAbgvmI//f1j8+blSOFVOsRi7t4116kbjWlsImyIAv5OSg4yr1v3hmmKqCk1RUonaF7kAwPJvoI3yenGGsaS6haanJNmBgYsA1BwdbW8tzE+PngrJKG80FCB5T2p798X0rWGrAo6oAp1UAU7nn1/VtpPwjMXLlyQtUOMCE36NinHm4nIIg8cwJHftau1ryAJ4QOz3ay5+cX08im6KdITiUi0Xj1DWFiCA2btcZH654D4CfcLT57AogRnrdCv+A/0f9DF67CQRVva/slGy+52w/YUYzI2llLMrX27wHw2XKFCaS+Ikycjw2+Jh4wRPybDiyyl5y5YsMDyQZ4+/R4a79jRpNgmpXsioRUYKvnz41zy8dEOHfqNajacNWeOXjY4BswegDo+nkNt9BNOF5XeHzx4QCTxRqNVOXFFKrfoa9coJe7FrFkKXnkW/rtkvPSRwDQd+w374eZ8rv3cHle3Yps7DDuq8FUW6Rd5Gj3FPTsL+0nGzznjOcs2Y/39SdeDy5nz3YkT9rdpYGFZvhoK+pCiJ7ymt5/kn0AlpuqMYaBpU5FlNb3XDvsHX7nygsG4z5X2LagR+MwbUVROw+XLp+O0RYpwpBzs6WmQtRnz8CG55WRKuhkYS9eEa+Q6Wt47hVPPrjYDAug5Gs+dyxIDskcPjayI+eef0RL48kuNrE03AUM9ByMP2nntO3bsQFWaWXWRwZBzXv/3evh13Lhx0jZfMinll3PnynEGE6wpFlwI9lm+du2sNZ4fxDygELle0GvatrVWbQWm4PB5OMwmhadtlUUnRVOurWWGtNlUY2s77+IihKRNU4vqgaziX6bCy5k4ooEvx6XKpSbTJfrGDXsuXzdtGtXn/K7/PY2UDBZ31detm1WgX7hzB604K9TMN6JvEK8XvJG2SdqCp1Jryh49elQso4SbT0znG95uSG8/DQcP8ozdxaMpmqYVuApgToAhsXHjxlGjRsnc/66umJyGSojJuT1Z4tyhil5DgwZiYUa62pTKetT3LnHoC1SyC7jvLqPutQfuW+vnkyexLi5a0cmdkh1Qrhz2/NChNPJO2QWGT0o1j0qUQB9/oUIaMx+axTMiddHNmzfTr1Q4O0YSWKDPU361pkgRy26//vNPLJVOTZXevbuGgRldup7R2rVvVJMnE+NCUFyQ2M/Vq1dDr+bPny9rh4Sfy/9R/gedOTkwjuexn599Zu0raHsd82M2a25+sYr3b8PfqTb32CSiVFq8GIV4u3Rh2uTPzbifr1p1XuAMOGuEdsR/oB+DiShEx2UXPQRpzoeWPCZ6HjSm2vnQcoSvSFKm1RdYyQvBJtvHGxZRLZDDH57cy5eJGV5kqfh9Fyt4kgeqfGKg8Tp19IptumqQw3SXYZfxwgXsMzORjQcO9FEtY9lscvGjDguwkHfO4Tm2UptYbqiB8XhQrBa6Z3vAmUVbfvvNbK8/fEgRYQphf3oPunhU5xG07ozISJ4rbNhiIib9FOAK1OXr9tD0mPtyLrQJa/fzhOcZ7idgfWizJFfS2rXHPnmiZU4g4kkU6Q5sXzIJ66J73mQiRc9a+lrpunax7mKJfol+82aObbEir3w6npEg6ObPNxeXV6tSIwBDljN1M7PkucPKiBjL3f3yZWOpUhy8ygvRIiN1lZF2LXz8+EyOJY1JU53DgTRUh35uPm/eNMslU7AjczFqAHlk0ZgHrA+IXyxiNhhMpUuj2bN3r0HWJnnfFYW35NiGYQAAWLpJREFUFa/91sNbMNmbd2ueT53vqv5qv379pHw+ZgufVTOH9etn2RTBuGN17M0fsP/aJ4dPpvochCOjR6NLIjlLONVj6t4dbFRki+ILpZl/tT0CRZ1gOtuImPEsl0ljB+U/lfAamzVTLOUExA+vqSwKlsP9Yvp0ey4fgNqiASoi7rR9P5NiYrSlSmEisqdnlqyf2j59EIQNG6ZwyYkR5XXlRS5CaZvr16+XZnKbS3gZPdTu3bvpuR95d4RkyO2PREnWOF7brdvPo/CeDLzcRDqWnj9/7unpCRsWBangAEuAlHkotydL9qPEiAgKqrz86aeMRYlJ1uPzwMK0s5QP/tySy+tj7Ju0HGmTS3esrHcaNbNgZZbe48doSPj5xVp7RmDmwQ0fNGgQ/Wop+SeeQjk88YIga+opkwSNkFR+w7F9OybA1KzJp+vae/Z8qnIIbXALuZWr6Kq8TnxNnyc/JgwPnSSPA9537oLJjflu5rsv3E/J4WGaKvEajeJXXIm6gpUDZ626+cUq3nuCPPb49dfPSW0dXv/6y5wZLuL+fX2R3rc+X/8/0I8HcUI/TXhq52RroEE6fFhzUy2jLLc4KTpa8SsM+/fbqSgJa6uvKh9JfmZmkSWiKGkYXTzCwhKg/c8+0yi2SRULy/TL9KzWSsvKWAGZuTqhot2OpXdlg6PW8lrwRWt2rbEa5XjyBH2oefKQ2vm3334Ln/ewkGg1WZdnjwsKoqmC+jgsuPgPgn4ixKyjr5PeNsXQvDPnDHstgANA/IosAc68c0NDwx6mHoCtRVoue/o5XTddas1bcSEmvf7zT3JX62vUIG4HG20az583Jxazik5R0dMQb7D/2qUMSxS4JQZbHBg1apCCbJpHwtOnmjZt6CwUueN5Kmd0VDteMF7I/HPXjR0rU/iSHc9YwEpft25STEwmxxI8I/IpRiZGUhmPNaVGeUQiOFjNrF/jiRNZOOavXxfy5eOoiHnbNgPj1uCkSarmTTr2MUW67Lqfgs5N49a0N1ZJnvA+cezYMdq/xeRXsz1/7x7eVSV6HBKsmTwZSeizcL7HJ8V/pvlMDIiZF7rhwy0rWUlPo4EapaP3Re6z3WwDQwORfMMq7r92Tc12CtuRog/JJbwA/e28cEwfsskgJ0vJuFG7KBF32q7tw3w2lvlmreg2Xesn5nhkywaLj2Jq3MhnKA0Jt1GMo6Yksdy/D4Ona9euYoaPt7c3IS1i9ZFGomyHZax3Tuh4tgJF3rQTJpgs4GN8fPzFixcB8cOuKs3tyar9yEwI5uhI4ZoMtAkbpd9n+SZOVTmGZKNqHxl178fYN41Xr5oL9qynLhv++gu9fvapOkr7aTQaKYPr8uXL8OuAAZhWcE2JBUtg8br3qVnpPiQkULgsPnViGPSU6PSuXbOXpz8h4QMVNgRq39QzIHFWB1MHg8nc7OjRo5H41d1dbISWuwajGrTmW0vbNHXtivlyB5WDpVFcSH7M7FbduntM8U6KVbyW/bx0KYp4peFVq01xIQHu56tW9ckPBgvmBOoF/X+g/wM9wvsx9+2cGOTrvSRckjZCYyvxjXLpLVVEEWmU7SM2IOC0qgo8turV9RleZGEddHNza9euHZmecqdC4gdGNqgW62akbRJwnKqbqmUmsj65LL1eEaTs9BiWihVHHad2WecCg3ujdTpnYqwjgyc4OJjKi3k+7ZQMEysgfv7NNxRIhV8zFvrMWtCvM+kA9CBieH8uXW1SEV4hrtANIUU82E/wA+txjX7N3JdzB4UNAqxPLAHiT04u58a3G6WqZzb6Rjxxew1707x2wPp6xsMNGzDYACbBqpQ60QiIkpMfkhU90yTuFFvwMHqQloKs3MJ46BDlJMA+92LGDGuqnOa01xMnNEWLYoeLFJFmYlB5KJhP0lypjD13w969OFDr1VMuamTQh8+bF3bWTI4lkhrIoc4Btgq6Epmx8Xr5cnva1P34I7qKmzfP8jG/ZYuBavXq1OGlFEayNmnwA/q33SaYuN013dHzPbcu6dd8/fXX8GaPpB5X9HFSQrNlPvrJt8fRwD6mkmrbZX6+n3h3ApqtxleTPndNap0H/LunJzESbni7AT4PgNJGm1QbVpgrnKbWvY5Js2uKFLFB/E8lvHzBgklRUfaudEYjZXJLKRoVD0qpBxOXMjmPGI7Yvp/IqMZ8LiT3kZn1U+OGycqAmC1PP/ruKBWkBsYp57UTxfO55JQ2yp1YnkznYE5BiX1CvF7wJgP9BCwFffAqj8zO2q++ssb7/iEpSZrbk4X70UtGRa0rXx4mRXrbTHz3jpb0sIEDb0TfqKSrRClSGdjj0ruG8MyXbLBuoGoYa03GNB9IP37evHk+Pj5k+AlK9WCUF/162bJU9i1zKOgqVbK89kGDMLNo2jSdndd+504MabF/YDnh5Ckeox0jzaaeLhGgJD2c0ptK/2X4S9rmq19/lZqLlllendfivr9Yt1jxTopVvIq4rkgRnrhQLR2vgPvLIiW16qL/0f9A/4eupq5wL2AnsHNilOXLwue9jd7SRkjyLSFMmVlfz9Swdd99l2bjSdHRWx1cMee+g5BhYHH9+nUYcMOTfVeW537+OY54gyHess0/9H+g9KZ2gJluKLm+zaUYZhxdqdJe2uauiF0ld5SkwiZr/dR+8w1e+wzksDtw4AB8eIoVZ6p853v0CO1WljdlbNVKugT/g6AfjiWvl5Chb3+bIt0eadDa7md4QjhgiNWvV1fVVSXo31poHRwXbLuf94X7VMoswo40koajosJZPShCkDZtBF9fBeeXv7+aVXQavb3FNknRM03iTrP9adJW4ipJmUZSJzxxMCmomEtXoYIiqoB+PofPUD/btpX1E3AzBUyq8lUzWyPB82qWbfx34FpobZZu1lr92t2G3ScNJ29473tQMndItnSqESsdd4W7BdTY4UX6RdRPym8xffVV2m1yHNg8OB1sZtBmeMxTETP85MnDBQcLim2OejZKlM2y0eZQ7VAyxlYdXkWMAvDavXt3aQQ8ZYlgwsaWIe9Xt71y+aGDShSsyZL53udpH+jbHN0cM1pmqRrc55/L0TlJL40a9TbxbR4uDxiuNgQQBocNJsVGu7AvI0gwdepkFZezEt7wiRPTtS49//ZbzA/55RdbFy+hWSTiTnhN836+WrwY94K2bTOzfhqOHMH7nD9/wgs5FTXYkDm4HNCZdW+sMtisWbMGdVgXog5rSEhI+/btXV1dAQjKnvvE8Im2LTSrm6ZwnQQWYHKRrIqxSZOEZwp0F7Lcnizcj5Li4gwNGpBcV3rbDCP1z5o1Af1nfo9L1xqiY2U51uhfcX6x2tLEt28zsC75+vrCg+7QocOWLVtE4i/Lfr5lvkWZ3u3r5cvRbzhmjOW1HzpkYGKjnJ3XvmjRK8ZubE6+BYOKRuyfhj9Z6DqQ3KxUYQyv8L6NW5sivmZSXbGd92fP4tBq2dLyK0i0YXk/jNK007RTvJliFa9iP4kIFV4t7yfg/q7bMUS/fEIJGz6Ufx70qySHPX/PGOgf83yMtAAozfnwGYehYV8hlUNFyxjZ4nU6ZeA7ZgzCmnnz7JlsiwqOhyc3emDG03t27dpFxrG1B0mD4+7dGMs29xr2IsoMwJR6rmhRsc38qOet9lHlp/oS+vy45+OKHiqKOf1zrOb080w4A1Z8OGvmzJnw4Z1WFMoU8gWZJ1hTuLAshPLPgv7Xia/z8fngLj2KfWRPmxv1G2XCOvb383Dk4RIaLAPIxeVa/GpxfFK8tRYW6xbDx7pquqbr2tGDztx4XOHClrWMZKxqvvxS2iYpeqZJ3Gl2eOi+hw9X5ivrTFaDvzH37+uZwBbtdlLRNIxIsOwXGxEJwPrExCLF/Rl77nyrVmcrqQoEKou2APosxBeqqKvYyNCok6kT4Lw+YX1aGlsuerVITA60PZb0gp6SAztpOon9jNfrya1rm3oFT2deIk2DBh9pzOv1AjH3i8Lblm0ejDyIe5LQzkab47XjSY3Bw+hBwT3YEWXJuKlC8wwEW9JXv162rO1WVZo5M+m69leJr3JyOR3Vjj6CTzIaNSAnmIODTPFXw+CXgbHUD382XJprLjvg6ZNyHxjedmW5+PhomPEmY2k0I7/kEt7Yx4/TtS4RntDXrm3j8qWCSkTcKUY8bHmR377lWaaTjULhNLvH16+Pm6CFtIUuXkcZgyW0JWy0eefOHbIbBUGgwrBpEi1Y6fMtoiliQ+rOWvdW6FeImutGLy8SltGWKxfr7y9rQZbbk7X7UVxgIPFVpCul7c2qVcQfaDsO+ZH2TaTkdrAq9KabMoXyhDO8LhFNJ7EJ79+/X7GflLQmG/xgV4skoRaBMVOhQrjWTZ+u8/Q0PnmSBpucqytKGR45kmJQ/R3xN4oCqZ3IkTdlyhSxipIAWJ2JdYZph8naTHz5krKdLYu4qJj73jc9ASrA4smbFLIhxCpexX7u2RPRsKEBXhXv58+B0+DcYb9gXa813P8Pg34pTJfhe/F9loD++a/mo+Pn5Rw7JwaJH4UIqRgYqMIvzgotA7GAG/76S+qM79ev33ULnjj0VZRZDcNr7sj7GQapCxYsgDG3bds2aw/yq69MipSgJqZ8hKUkvujm13TpIubAoSJ3thCRhIc+X0dfp+CZgvBdkxUpctlugd56JyfYUPV6PWnc+vn52TngAA7qypWLefjw0yxe9rc5JXwK3CWAAmm2CbgnhxpdAvN08zLWT9jGRj8bTbizrr7uWeNZxRZoOVitX53ea5fmymtHjEiBPgCGSpfGcbt3r6xNe4g74cNeRi9YE2EJg5uQRgpBfPyrxYupMEZTvHjk4cPpqj2wxP0Ze+571w+hlMqSXMnB2sG9Nb1dNa51rxYte0nl7APjOJttvcZ+Yf1WvF5xPfo6Z+IU+0ly0aW4UoGmQOn91DIGDEU+k5R+arUcy9+wreqdyTHv7m4AxA+v1tp8mfgSNa24HCIpuOz4Sf8TCeTtMZgzeYYMGQKzvn379oq6HJjgxCI5AFzk3fvqq1+HqETBmiyZ75Sr09HUMVXAiZE2puLJCQighUtQq+Gsa9HXiBIx4UOCtR2kz9M+9q8hiiyNdIglvOldl5Li4giax7E+Kx7Pv/4a13AGl3WCLh+Xj4T80ryfL+fNs8GzmWY/9Zs3m7kduVTRksC4wNLa0lQq7RfrZ7tNUmu6ePFi3759SVZc8bnTIy6nLRedFG1/P0l7keJvCGQfPzY2aYJI2tk5VQTSIrcny/ejN4zhmitUSEiOY9g+wBIjJus0C0U+3r7Js3tlWLfOIr5joFXL6OGR4XXpyJEj8LhdXVHiw9/fX7GfYCpjuYiTU1KsuSwY9hQ+H7oqYYNTvPYvvuClK3iBAlzdunyPHpq5c1/u3Bnh7R39/Ll5skdFJeXMicoHMm6VMVr0Fxflit4T7h0+fBi6N3bsWGh5zNgx8L74nuInDSct76eO8ZrE+PhYuvmJtIfEtncbdlv2WazizcAzOmhEf80XnrmJz0cR9/+70nusAX07cb+Nj1G6AuAqOycG7f1GkzFVAg/zZ8c+UU4l1JC+jCQoT0QWsBGKXBbiTe9TwR2G4IZRGWdLIKIxqn1RfJAk5bBw4SvLNoNMQZgl4o95jbpkFiofHzRzizn7Iyb74gtqMyIxAm5FwWsI+keOHKnYSSLQ5Rs1glNOnz5Nn/zEAP1jtKmJ16AKD+ckxNvKwrouXC+oLoiEJ9pRmeznxaiLFXQVqG71O913MlgJJijAa/iXv+CfkWuXsOLwVaoIFy/icr1tG+495ctbcurbQ9wpmISGfEM0jbTD7S1ECw4WWrc2Z/IQww+jyrGHZUiG+zPw3FfoV2RXo5JAly25KCaLN2HLFjXj7TdeuJD4IREgb2hc6O3o26ffn94TuWdq+NRWxlZfGL4owKeqyYbFuyZfc5h22ErDSrB8YK0wMb5XIgo7YTwhu/Znw4Yh6l271kY/9cuW4dOpWfOfGvPi0dTYFJkM3issUBvfboR/wbKw0bBRPFcU/LLWJvkpAfrLElEAwnqVNpNc2a4/s//aqfN7I/emcuq3by/zreoZVSXPEv3pxCq6KnDiyfcn5a7ZpLiSmpJkA6frflqyNNIhlvBm4BmFDRlioz4E8BBZBUJyKWRnTWfbxJ1SDyVBqJgHD9I7lgS9nqtQQWQAE0+5F3OvqKYopS++TXybZpt//vknDKSpU6fCKxgAghWtD5indfXIErvg1QL7++nCu8ApUkoAWHZIRAKgmKj2apnb8zH2I3JRa1xd044aPXpE2XEvZs78B/dNPZPH0rSTJ6UYdu3CG1ixYmbWJWTCYTJ/Ay04bVKBaSbvI7pOor29cchVr27t2v/8Uw+439VVA1gfEL+iL8fZmW/Y0NC2LeKfqlXleRwGk6GNBjUEYbUP0AR07NgRLJNLly5BV1t1aFUlsIpiP2mSvt20ydLN/4wJK1Fd5UidHClJq3gzcD8DTAFYNhOaS129qjXc/z8F+k9aP+Z7oZ/mi0dfnLTjOHYaCUNyhOaQ/d2PWW8XV65UPMufeUzPr19Pv27fvl3K/gurmIeHh/jhesWw4GJ9m1knM3QcP368Xbt2MPiOHTtm7TMVK2KCPrwq/jdXKIr8+eZLuZy1ay9i0L+sXyiTtTi3Ywf88bcrv8HHqt+sTuU1ik3dYYsmvMJ7in/99NNPJ/8njlY+reDy+97pa+0De87sKR6IPJVNfZt6nvLM/DcePX20993e2ULR5iwRWGLRlUXiv368+iMuPY9rZqb9i2vXBrAstVAnp5vffPOY0QveHDvW8pOLL2MqUVn/sjZa++7Gd1jaGFT44OmD6eiEp+eNCRNCs2enbnjNm2f/qXvP7HXxx50bXuF9Or7zpCc8R1rnx87JFeqgOr9hA/z93LZtwYwR/+a4cWm2sP78+qk3pna+17mif0VHZjyIP3lC8sCjyRmCamLDbw23PP36pEnwQZ+WLW3M6kBWY3N19ux/fOQPvo3561/d+0r29x+u/eAA906tmnhjovTvK1eu7N+//0orayMcV1ja0uO6dWWjEf4IV+0SgM906eWlme/55vPo38kdkhuWcenf7/bsCd91a+RI8S/3v/wSJahHjRL/MuoWFjM082lmedVpzgXF4/Thw/RM7/TvL/7xAvPywqg7bX31tnFcZZWgT6pVU/yvF8u99q9YUfzLpBuTFC9K8bjL2DZ9mjdPb69ushKFgFKlYBhL1xB4EKiM6dtY9jisHVu3boUdBHY3kqCx8cmll5aifyTU8RevX+xpeefZnejqCskrX6g9PWkLw8fUty/8eo8NFRgwH3WKnd21K5iJ5NywvfIcP/6YeRsf16596sSJf3BNOLNvH1EPndm/X/p3H2bBSudRxg7i7YFXG5/xadECvuva9On0663hw+HX+1aQieWxb9+ZFSsuff/9tYEDb7dp87ByZb+8eUOkBkD16o8tzzp45mCpgFIoD+/TYvz48WIaUvXZ1Ud5K1/1Tcbc8KBDB/Ev57ZupbsHb3DBvISijQAeZCf+dBWDqA0eNcjwbSRAsunYcn+20fu0avXJRki6Qb9ibk9Wefp9YnxQa11f2x5r2E/wIw4WmVVkZAPOWsojFQaZAgKoEfJVLFu2DFaxL7/8Et4PGTLkNpOJhg+7fIaI/HaXcRmz2qEdmU1see6+fREODurs2Tm9Pt6yzQohWKl8rlZuUzLR1aFDRuhSy5YaLRMM1jMd6V9f/Yo8P2F4LXAVip00UoiDUXYQ95Z3ckno/9eefjjuxNwhnY7IxEiFEEfS+0aGRsSMay3ZI2P9PGs8W4OrQQvRAM0AShTpq0XMOlc3N7PXzvO6kSPFdQ6JVlMroYreTdvEncZ4Y34uv5h9mN5rj/Hx0ZYrJwuA2vOMRH9/TX3NNBUPzDUnJv4r7VeUkfKH/g9t3744wn/9VdDrKatb06lTeu8ntOlh9Jinm9dN260UV0rcOMpwZcjrL7+fwcFmRVUrR8TOnfg4KlVKU/nyE8yjW9G3MANQV0n6x1PvT8ENxMR3/c/pbTNeo0Hv6eepmEBJ+fjZ8OEUVrJdb2rntc95OUcM6qZKPiE/pWTNJBoDSvgx++cSwrKzADy8kbbZwtgC2tz4dmMG7qeMpfFD6hLeDDyjpPfvMSPcwUGRGiisf3+KA8iq/20Qd6bKAwwL45jTJ9bPLx1jieNIl8OwZYvYpsc7j5wc2sBDwobEJ8XbPz5pE+nQoQPHcbafO0VmMPSnq7rg1QJ1nNpGPzcaMELlpnGzViRK+TNhfftqmf9OmtvzkfYjYr1T58olSBgq5S5wlhcHE8cag8in3Dc17drhyrl0qTQKQSkr8CaT69KRI0dGjhx52Kby+qsFC6QRD4HZ7ZgpmolrDw9P8PaO/uWXl82bGzdtUs6Vvy5cJ26GMScxq6fdl2iUFj1e1FfwVWyTgkX6WrUs3fzmGgmTQAJ8XkYva1W8GbufXTVIWrNGv0Z48kTbvfu/19NvG+VnHvQDOECXJF/YnsFxV7hLWbmyGyQwMrKoS5cUgqrR0WpGhkctXLx4kUTFQ0JCCKNTzivgZrABEhKSsjuqHVShXINmGZvA+/fvlxW5K54+eDBm+EycGG7ZZot7SOW267sUFcwNG7Dwt3t3rYGi3oyzuaOpI3zscOThjh07wjdGWRCcJUVFofiioyMAR6JV7t279z8IVrK8zVZGdPaveiPPRU78kNj9KfIVluXL2kk8kq5+6gX9j7ofc6px1/yM+2yjfiNYofAeVp8suXYDQEyWXs+XL2+tn7aJO3s+7SktV/2UzyhduP9ZwrMvNF9gAom6wCEjZt/pmYNZ4+amZfCLK1XKFBiYyX7C6r/asLoKX2WXcZe1a9cwlAnoX6kyJlHHhMP0q1f/42OehjeslnDTRCB1Lfpabg69trNezMpIm4mJVM6RGJGyrVJmBeAtEqyBu5fJa0/6kFRWi+4Mrygv2bUbDh2iZc0MVqjatXhxWZs0qpe9TmEqexjzkCx/MPIzdj+lLI2yEt6MPaOnzBX9dv16+SCKjCR7IF6fKlHKNnGnrBGwRiw5Umz3UzdrlpgUSseOiB0UCpsYPlFKRmxPmyNGjJAS09l47mfen6muq06CDPTTzNhs3Zt1foJCRRnxKcOiaq3NqIsX6dEgyC5VSqbC+ZH2I6JL5uvUEZQo8CnzEKyR6Js3/w37Jq2c4iTCvxCrT+fOn2Zdeufhga7Vjh0pk81s/YaHf4Jr32fYB0M6W0i2Dl1Rq7RF1xbtufbW2kyKiUEbMls2mJLSbP44LkVArb+2v5RhzLKKN2P9nK2bLWUa/Zfm9FuC9SwH/bDuEPsS1f3YHhBgexEbiewGEan8+9OnLdsnPxaiB3YQX/WGDRvENrVa7aJFiyjVZ9Kk6TlyPPhMdYsvVChjE4NU60TlamsP0s8v1sEBoB0XFpYga7OPR2VM9NyagtgWLUKZt5EjdUJoKHE4xj81EaO8EC/0798fvvGZBbtZ1OXLuArURuNh7dq18Bm4zP8l0H/83XGqGJOV900In0DakFJK/izvJzTeVNNU3NLKcmWz8NoN7u6A+A0StRFZmzaIO4lyOz+XP4Ug5dM+I8D9gPjTxP3+sf6k+erCu4gaAsKjR8hEAYPcwQHLqk6c+DRjScS4lq1FHjyI88jFRdDr/w2gH4uCwgbAffvrzV8EfKmk4dvnGVfL1rNcsph79+RWUEhIfFI8sbLeEe5k5trJeIAnTkAzVWL0/fu4RBcrZsapBFaSHf8pOaLvT5LnWPwLEZh+/yLjIk1SlkZZCW/G2qSgkGAReo3YvZu4j2Vt2ibulO9lej1MCpgar5cvj/b2Tnj+3HY/BT8/jqWpGI6a2cF/1f/qoMYcsHkv52VgfHp4eADut9R2tNYCrMzn3p8b/mw48a1Rvc2Xmi/XG9ZLA7Akj+1udLfRZqy/P6nC66tU+TT7kRASwrM0DN3kyfIbe/06x0os9AsX/kv2TcQGLBAEs8kc42GFHIZkNdyP3c84nsdpW7IkYg8mGSYl8/nYmGG+DrPEGw1rBDin4fCGWwxbbLRpaNgQfcReXjI3v9jmJv0maK25prm1Kt4MGyfQQhO+yb8X9FtD6lnL3gMHeYDskao+bTwtaq1LW3jaqxeWzx87Ztk4RXP4+iiA7O7uDmOiV69epCMoPU6ePNm9e3c0E1t81fCzP9Hv9fp1BibGmDEYYzp//nyaD7JXr6ewCs6c+ULW5vhlKDwx4/oAsYXvv9cRuRW6Hzp0gL7d3oXE83DfPqD+M5oxIRbMRaRDoR2DZuXIkSNlfAv/A6Af0AMFkQ9Gpgjs/f76d2LYvBF942P3UzAJy/TLyGStzFX+lNdujbjzTeIbqmtcol/yDz4jwPq2cf+FqAtktTbQNJBFY3jmVid6wU92P8VsFsvWiM9UL8nK+MdB/7aIbUiq87RbUFwQOVPBDEj8kHG1bLJ5IvfsUcx36qbtZkOwxs5rJ4A+9+VchWsXBAptCSz6SlpC+o0bZW0CgiylxWSta9HX4NcXCS9gmmdTZ7OdOpI2WElmadSzSkSxhDdjbSa+ekWOQyn1LbbTpQtalRs2yNq0TdypkHbCmDfFH97ZGRBM2MCBumnT9KtXGz09pTkDxFWtcTOnzUzTIWkggH7L6OjHXuffJ73fH7m/q6kr3Brqel4ub19t3/2G/f4mfySkUueQCatZNhJ14QI8I0s5kY+3zqPQMksAgzcpo1Wt5tlQ0fTo8a/aNzXdu4v8fkZ3dzSkS5QQk4Q/ej+TknhmYSaEh7+aPx/T5CSkgp8AMwzQDCh2oBgg/nIHy8koquURM6aQA5azzM0vthkkBFEyIbxRrOLNWD+fCE8onQ+Qw78R9KssDsV/ZQnob25sjtkR0dfTHBxHDEcwUKhpJt+0mDRG5P79lo2/Y6MfsLLBYCDSsd27dys2HhAQMHToNHL5/1qlytvUiYP2TAxBECjZhnKHbD/IBw9QZC5fPl4koiLvwq/DsFR0qDolw3XkSAT9ixaho1HP0MnyXzAoPDBsIJw1bRr2+YEFq4PAkvwMW7c+efIEPtCpUye9Xv+/BPo/JNOVNDI0ol8B/RMl/6HIQ5+sn3sNewHxi0K8n+zaFYk7v33+LVY1GVtYW1Y+2TOygfu3vN1Ce3+/sH4iUU9KEjIryudKl5Yl0H/U+xnr60u84PLV48QJyiiwoXL/6eeREC8gbOLzEt9iZ1Nn0fbLWJsvmXP95VwzIn/LUhfAEqBfV+pX2hCssefaAfNRFUpIXIhiP3kmB2E8dw4QldrJCWCWYlrXzy9/hkZGPBsB75e+xmpRwJGZv5/E0ogYukABmRBsBtqkbOaIXbtSzJXwcMIWJIyVKv3GJnGnQtxp/37A/aZu3QDrixkvsh+uQAG+bl3kRGLa78KlS7AaUAoNdGJnxM5/cJ33E/wW6RY14BuI3S3IIcFaLb7Wv3M/0jGtWQz0Je/pxACO7Ctq9b9q3zSwUBUxjGmZGa+TCHF+gn5SDWEUjDdGQv1OwhP6CfZiAPrFOayUrcBVsN1mxI4d0L2nffrI3PzSNgFkYtFtsraPVIs3M/0kDXtrOQj/ivSeLGvXJujvG4Z1kAciD6Q5OHYZdonbj7SFZyNG4DqrJNj5dv163LaHDiXJBsD9BoPBWvvLlr0qXXqDaxvUshnWq5faOuOy4un379+HE/v27Wvng+zcGQn45817KbZp2L9/UztcCr/UpEgydeuGCr4bN7JuBwVxTk59lmOIds2bNXAWKaJfuZIK/CXFxXF58qDz7MmTnTt3wgd++OGHfxysZHmbUUlR5Om8Fn0NjEaqTlvxesW/rZ8fo01L4k64A2Dw5OByBMQG/Bv6aYn7kz4kzXoxizb72S9mw6+W5xr37OEqVzbu2fNJ7ydjqESBP70+1TbGCLDfrFr1bxtLNfTmavJWxlYwCzLZJskSiyj//7V3JvAxnP8fj0Tc1E3d+dE6i7ivRiKJm6AUpY7WEWerlRbVFHW1jlBadbT4U2cVjatVpGhUtY662dnd2dlZ9xkJQuL/ffZJ19rd7L3JJvl8XnnlNTs7856Z7zwz+5lnnuf7mOQwPSWfsjJgjT3HvjZhLW/Vnd5+qvQV4RLd4/TNY5RGI6AZc4RkgfakgFDgdspt/n54d+Jut8RT5A053NF0hP/iXOnWzWSOrmNHi0wriTttFiF6nHgYH08PGOK4capu3cjr86wVz18F1KypkTXdVd35kOSrpFVecq87oj0SJUZVFaryHa2vrO+d92RZFJX6xm+q3uzdu0bfXVUoVEj+b5AfL/rtEEUFH8x4926Fvkk9H8ozw/bzemQkq0GfM0fQN0I2ftmVMffPH7U/kuPfot1inZl8/jxviWRSzW/MnCyyrAO91WkNLkx68Tq9n+1UrCvmN9I3Od3087GW5t+Zb7NwfKv51jBYzAulTZ+GyST3alolln5Yk8vjxnXr1o28r3l7RGONHn2D7kATgmP6Nm7ME/lv2rQpNTXVzguDD2Mxfvx4O0/k4cMPaXNFiyrv3Ut7NS++//722uwmWEuoZSC0bKmiWZs2pVV8qkJCAvayZf5+xEYQmzdvHm10+/bt5o2aNDVrsvI6diwtsHHjxuxnfNkzz63PWOYHXRveu3H0jdHeuZ9uZ+5PYuO41dGkZSF4lPqohsje/1BAvGc/jX2/5omGP977C/4r7q3wtnjq9KmxDE1ceHMC9ttQqlRqYqK3laXqGtZbuoyqzN0UN4yW/ejYMXa7qFuXfzQZrYwWtjJgjT3H3lbX1njYdfP95P22xagoUV/3Jn74YXrMNnIbQkVej2Rt6sRXjLuiuhLPh/v3k+N/qG/m62I8n8gy65GSPz8Vm7RHx9dfNy5aJiuS3Weva1Qd3Nbs8MwZbWysZsoUZe3al7/7OkwVxhsV8O7C3navi9HEUOlaJC3y2nuyfPAgb34mTpjA8wgZjynhVfFU9+3LE/YbhrnIyP28+/XX7OFWP8qB1KCB13oG1hLpv7dkxtX8xkzefbSUUIq/Mzfpxev0ftKDLnFGiCNyuun/4s4XFIgPb35o80TGSDGGx68XGmnp38HdXbjQHM6fBxbrm9oPGTLEOj8igrWzXztsyzlf35kREbypT58+fX7//fcnT57YLHBz5syh5Re/ODCe9cjwgSdmzbrDmaoWLY6W8DGkJeWqUYONXcde0up16qtpLN31OT+ebW358uW8zZIx9o5+LKHrw4cLghAaGtqmTRvjFkfZyfSTreQV/PQXcSWCt2zOCabfJHFn9K1oNm6Dpubj1MdetZ8G359fmZ/nWvkt6TcvjOedL7/kl8zzdhrBwaziatYsLyxLe5L21NDU+CXpF7cwU+7f5yPUPktJeaLRMMdQrBhNG5jpDVhjz7HLT2RfhS9dpLdT0q35k+azblTqnj2V+ucNyWjMRBPauoR1vDcLGwD77kLvvDb5CF98iFYWT3oGKFCAZwsxZ1pJ3El3s5tPb15KvvTnwz93Ju5cc3/NmBtjWmtb03+apjk0n76lZUxy0RqaJjdVNmXJ8YTihqHEs+h9PnOZ4owZ7ALx9WXWf+RIr91PnghLoR9JXfrmmwzez4eHDvEadJa788MPvfm8S/qWSIKfX/KLY1Qbr1VRqEjXzi7tLp1ZL16n95O3VWmpapnTTT9/+ctbqFs/eTM0M9gAq+JgkwDdjIpKbyjEK127nvT3bx8eTs54n/FI75YUGMiSYx766gBrGNOmzR9//NG+fXtu/Tt27Pjpp5/GxsbyPDkWVx81ahQtuXPnTvtP5N69SbTFUqVUiYmpsigq8uW77JvLX8FSbhuaO5cuzcarO3EizfSvPv816wO+Lhfvarxx40ba6Ndff22h2vKHH3jf5cjIyGx84+Zj5ZZWleaZ+3LOj5YhcefZx2fzCHlyKXLxjjFe+GDGu+0WVBY89/icd8bT8HIs7ePhw8z7Fi3KE1lm+7LEBxZ9olLxpj50AzFm8gwK9CvoxH7yOp2eV3ta2U/e71CpH+pIUbSocXcOU2OR+pBnEyqgLGAyjqy3PUBe69/fMH21d28rzEpCJV7Z313VPUQVUl9Zv4qyykuKl3imHXv+aElantaidYlAnL7qvqUFlhOinFDuoHww5xh0DzH5cAdCyZK6F5sHe9d+arVCiRKsRBQurFOrM3g/U+7dY5vWPxolvjgglLed97T0DPXqWWEOEgexymjxQ/NevE7v50n5JE9RbbHTXQ4y/byhQpAcZPNEfqJhHblGqkfqLHVEu20pf5bUuPGMatX4yLs2C0eJEqwhjfbPy4ZefUePHh04cCAf5s2gwYMHz5s3b+/evSZdY+nBgL49e/asQyeyaVM29taCBXe1sbG8hxB/xIyX4zkhd25m+g09CceIbBzHyPFpfcV27dpFG52lr4/87+J73kCZHlRMUohmvxv3Hw//qCpWjX8Yn9N+tAyJO3lX+MjrkV577OT1K6ormjh+r9pPQzcYngmRv6S+FR2dQ8qSHBLCfqr37OGvRo0rUHTpD1hjz37y9zw/P/jZyn7K+o7UCn0WHVXXrtaZr2leY+M5Sq9571u4y5f5EyNLCVq/Pqv1N2p+ab5uY2Vji1beV+FbTFmsmlitidSkva59v6v9elzp0Vrbmv7TNM2h+fQtLUNLWiQUE4oZV0/C9DvN1P72m1C+vNas3tDb9lNZu7ahO2/G76dK3zdG4edHDwDefN4TNm8mx28YO8wic420hvc2Me/F68p+8t7G8dr4HG36LyZfpCiQb7N5InnSsfHieJMAkd1nv9CTJ5vD/w4ICA0KCgkJIftuHS4IOv0YfELK42SeqItu2c9rK69fj42NJQ/NnT1Xhw4doqKi1q5de/r06ZMnT9KcCH0aL4dOZGxsIm23fHm1MJF1P1C//XYTZRM6zC0S649y4YJO/9z+PKsx71e+rI3PlYgIZnn/+IO2O2nSJAPQkIokJSWlc+fOPLcPbtzZj8kTd+YT8rH6PHU54+bdiKczxlffFvbBli2P9JnjlYUKpdy6lUOO/bp+eNG7CxaINWqwQU///NOEaXHAGpv7uTdpLx80w2TkVwu3X33ic1b9FhNjnbntwTZy/PTfq6/N115j3cz0eZCUxYqlPn5shfmF5gvy/cPF4YulxWultTukHfFy/DndOePGital1WlpeVqL1iUCcSZoJlRXVl+pWYnrPUcxpWXLlHXqSGbVfBmzn7xhm7patWwQT6VOmU+RL5ci1xBxiEkvXlf2k/exMeQFyqGmPyElgTX5FfLbPJF0W2QDi4jRpq9T58xhzcjGjzeHT6xdm1zvp5Mm2SwZBw+y5vXVqonsZXflymxsmsuXzYFPnjw5ceLEvHnz3n77bePq/549e9L/YcOGOXEi69Vjw2/NqMkyA0iLF0eoIugw6cZNq8fHs72qUiUtb4ZG1uRXsLbRfxf3FfLlS0lI+Pfff2m7o0aNMtAMScdPnTrF+yTghphdmdXF6rxK76cHPyGeLjL50BY33n+fj/thGFI+Jxw72X120xg0iJnUggVTjbow8eUtDlhjnSk+EYsqi/Iet7ZrKHnbHh8f+cSJbBBPnkBCatCAdRQZMgTXJpg5galt3pylD2rRInsce6gqlA+jYdKL1xXmB+IHRBulHpWjTT+JDyp5O+W29ZP3tvptWmy2ZrZJgLjNnRO8vGVL7ZIlz98rXfrnn5DWrcOCgsgZ2ywZ69ezBv1t2siszq9NG/6y2/qJPHPmzNq1a6Oiojp06MCt/9ChQ504kZs2JdCmK/gevOjjJx87NkIcQYf5ieYTWj02ljX+adAgrX3/bu1uPixlWkaIDRvUajUfGt1AMwwvumTJEvpq7ty5uHllV2ZNsaadpgrxtMlMOsA682hq1WI9L/Ple3r1as459sTdu/kgmuYDyvLlzQessc48n3yeDyNQSlUq7qHtrDhK3rWuXLnsEU/+upW9MdZnLse1CWZOYN5btowcP/3PHsc+U5xJdzA+/qa7msmtlFay1uzKoJxu+mtqmHc58/iM9ZP3hvoNlp9e85VJgO4tXUr31iZlf6fbLPl+w/wofc/amY0a2VMy5s5l1e2DBrF+uteHDGG++Ztv7DyRGo1m1apV5PjXrVvnxIlMSXlWPeASbX1usXdolWkalp9nsJr1V169mj2KhIenmf7pmunsq2uDec0c+fvbt2/TMXYzSgutKlOGvaa4dKl///701f79+3Hzyq7MnYk7a4m16D/i6TozNSlJyJOHDe/m43Nj9OgcdexPVCpex886R02dapFpMmCNFeaxR8dKqkrynlom3W3TNf2NGrEdMLtXZ93yqS5fnnVRKFnSkAcJ1yaYYGYh5lH5KH+RbtKL1xXmP/I/JukZc6jpD5XZa5RfEn+xfvL4OCYrpBUmAeJDrDUpHUfnp0aNtOF1Tpw4wUaibdXqdMuW9pSMceNEw1BZd2bNSq+9kIcK3LcDt9HWqxaO12p1yzTLDJmb589npr9377Se+Lzlz7J7y3gmOPqRTr5/nw4zNDSUc5IvXmS/NGXL0nMIze/cubNWq8UFDCaY9jB5ewwhd26TUbqy/7GnpAj6ZOSsZvrFkf4Mq5gMWJMec3/Sfp5Ss7Ous/HAYdb3U/ryS3L80pw52acsNWzImjo0bIhrE0wwsyiznJKNoRuoDHQjkydF+Ev+K0eb/gHXBlAUVt5faf3ktVa1psXWSetMApSwYQPdXl8pckSfo1ZITmYjtkRGRpLr/apyZVW3bvaUDDLWtPqKFaxeKmHjRjaqYvfuGVbgtH37V/BhDy1Ll2pipVjDIIWTJ7P3DyNHpuXuKS+U569Env03XOiDn37ifYsT9WPB8K5jV3v1Wr9+PevM8OmnuIDBBNNeo6ZP5SZZTeWWXY9do8/7Ifj7pyYlWWSaDFhjkbntwTY+bka/q/1MOu/mtHjeX7eOfD/9x7UJJphZlNlQ1ZDuZvTfjcwQVYih8jrnmv4JNydQFKbfnm795PHUZtu020wC9GDr1ks+vnl8L/BEZUePPoqLiyPL2719+3N+fqJZ51qLatWK5ev89Vf2g8fTd5incfVcgVNXrPi5T1/agVq1BP4CqIxQhlYfMYK9fyDrT9PH5eM8ySsfhzItA3S/fn369KGD5du69vbbLAvHokVjxoyxOQIxbgpggvlC9cHmzeT4E378MQceu6zvJiS++qoVpvGANeZadX+Vn8KPD4xtPFYuyieYYIKZFZnzNPPI8dN/NzLHimPN0wHlONO/6O4iNjrx9RHWT15tJUv5/Kv2V5MAJe7adcCnIpnjggXZ4LXz5t3kzdnXDxzIvPvkyfaUjCpVWDr8CxdYms6U27d5zr6MKXBP1Gra3LmipcuWZfuw8v/U9Nvpq/DVyBr+/iEmhg0IwhNo0GMiXytZENhOFikydMgQOtiLFy+yhwf9kJbX4+NDQkLCw8OVSiUuYDDBBNMmU6vvSqtt2dIK0zBgjTlwqmYqH0wq+lY04gkmmGCCaZG5XbudHP/P2p9ztOnf8mAL/VpEXImwHugAIYAWOywfNglQ0r59K3yC9dXkrDFMp05ryAST75f79WOmf+FCm6dQlnV58rC3BImJaRVUymLFDCP1eLpw3F+zhjXEDw+fOlXDc/WUFcryDuNhYez9w+rVzPQPVQ+lmVHi80yCUmAgrThu0CA63mPHjrGG/vq00Ht276Y5H330ES42MMEE0x7mvSVLyPHf+/ZbK0zDgDUmND6CCpn+BXcXIJ5gggkmmJ5jZgfT/+fDP+k3o5FkI80OH8zsuHzcJEAP//hjks87ZI7797/m53euVasIsry///47H21HWr/eZrhPnWLp8EuUUD330/puWA+PHMmAE3l9+HD2Yn3yZEHQlSjBKvurnapPRxqrjaUHAPoYG8tMfwNVA5q5UbvRsOLt6dNpxYmdOtHx7tu3L2HtWvqo69yZD8Rrf9seXGxgggmmTaZhwJp/5bQkyLJOHiwOpvtSbiH36vurEU8wwQQTTJh+G2Q+tmg5dTnrQSkisHT+F3QXTAL06O+/e/vMIHO8aNHdWrW+Ir/7zjuRz/7rmmY+dLa5du1i6fADAyUD8+qbb7JE+D/8kAEnkqUGp4eT2FhafuJE1oi/xIb2PDte5cqswVJ8vKzSqfwFfz+F3yX5kmHF5PPnacWpr71Gh7x169brw4axtj2zZ/NxA65fv46LDUwwwXQjkw9Ys0CzQKcfK7C7qjt9zKvIu0pahXiCCSaYYML02zb9T1Kf+Cp8ydFKOslKUMj10g+MKIsmAXp8+nRjn/VkjrdvvxoczPzunDnxNF9VogQba+b0aZvhXr6cZcaMiLhiYN6cMIGlrJ42zdMn8unNm2wwoPz5ZZEd18WLcpEiCp9PB9KRThGnFC7MexrI27TbaE4toZYJkx5s5gYE0CGvXr1arFGD9vng6tV8mDBcbGCCCaZ7mXzAmi7qLkqdkg8pX0go9KP0I+IJJphgggnTb5fpJ5VRsaY7J+QT6UWEvD4tQL7fPEDJly6V8DlK5nj2bFbNX7fumMjI66nJycxM587NGuzbEm9MP2bMDQOT5768NmiQp0/kg23b2JOJPv0O1wcfiD5DP6aDHaoaTnvl7y/QzMkaliR7oHqgCfNWdPSSChVYclJ9Mh9lwYLz586ljytXrsTFBiaYYLqXyQesKSwUbqJsQhPFheJ7tHsQTzDBBBNMmH4HTH8DqYGVZHCkC7oLPGGleYCun2aWvULp/2vTpk1wcEihQnF162p4r1Z1uXL2hHvYMNaoZs6cOwZm0r59rGnQ6697+kTeHD+eNnTLKKH+uXO6vL1i6GCb/9WF9qpMGWb626na0ZxFmkWmbzlOnVpTtiy5/GmRkezhISysZ8+e9PHSpUu42MAEE0y3M6sqq/KBKssJ5Q7KBxFPMMEEE0yYfsdMf5crXdj4XFK643PxLPVlhbLmATq8U0c/Qa0a9yKzO3jwO3nzCr6+imv7j7GG8g0b2hPuTp1Yf9mNGxMMTD4uvbp8eU+fSD7GVtKvvxqv1W3GJvaEs7sR7VXNmiztJh/FLV4bb87crm/T/354OHH+joqi6V69euHCABNMMD1n+osKRY/JxxBPMMEEE0yYfodN//Drw+mHZKY4M72IHJYP0wL/E/5nHqDvvr5G5jg88E2esqZFC9Yrd9sUVlVPdt6ecNevz/rLHjny8Dn06VPB31+RK1fqw4eeO5GpiYlsK35+KQkJxmvt/Dee1aX9Xp49zLRSkdfnY2FaZP4xahQd+Lv6h4fln31G0zExMbgwwAQTTE8w10nrqimrrZfWI55gggkmmDD9zpj+abenWRylzKBftb/SAnWUdcwD9NEHV8kct23WlvyuRqMZP/4mffyo016Wyubdd+0Jd6lSrL+sVvvCuPFitWpEeHzunOdOJG9EJDVsaMJU69TM9F/I7ZPrcteu6q80X9HH9qr2FpmKXbvowHs3bSrkyTP03Xdp+ujRo7gwwAQTTDDBBBNMMGH6vc70r7i3gnxtb3Xv9CLC09c0UTYxD1BExJXcuU+T2W3Xrl1KSsrWrQ/IwQf97w/WVv6TT2zGWq3W5crF+sumpLx4ttq1I0Lijh2eO5G3p06lTdx4/31zZrHLJZjvL3WkRw/1APUAmp4sTrbIvHv3Lh17p5YtT9SvTxMdOnRITk7GhQEmmGCCCSaYYIIJ0+91pn934m7ytUHKoPQisk5aRwsEq4LNA1S9uvjSS2wM2uHDhtHHa9eekukv6H/+oo/f3UWLbMY6Pp6NzFWxomCyS9dHjCDXfXfhQs+dSDksjDbxYMsWc2ZtZW1m+utse+01ZU2hJk1v1263yKTnnJDg4JDWrVe2bElBiI6OxoUBJphgggkmmGCCCdPvjab/1ONT5GurK6unF5EVEnsV0FHV0SRAycmpuXMLFcovI787e/p0PvOVV1g2nu0+tR/8+KPNWG/axJL0N2umMtmlO3Pnsmr4997z0IlMffJEWbAgbeLptWvmzHBVOB1v5XeXzl96zlfh66/wV+lU6TE7tWVNm8b27Uv/f/nlF1wYYIIJJphgggkmmDD93mj6bz69aZyR01y8XXtPdU+TAJ0/n0yWvUH18eR3N+qT05MGDmRde6N9Bjw8fNhmrBcsYBk/33hDbbJLD376iXUF7tzZQyfy0TGWX0h89VWLTN6kZ4Y4Y6N2I000UDWwwuyrt/uhoaFt2rS5d+8eLgwwwQQTTDDBBBNMmH5vNP2kvEJecrdKndJiRGZrZtO3ZIVNAsRb8Ic06k2u99h/ldzLlt2jmZ18FiYrFDZjHRXFXguMHSua7M/jU6fIlGtq1fLQibwzfz7vamyR+bHIxucarR49XhxPE8PEYVaYkZGRwXqNHTsWFwaYYIIJJphgggkmTL/3mv4AMYClopfjLUYkWoymbyPFSJMAzZ59x8fncpugMLK8N06e5DPPnn1MPv5ln0MpDx7YjPVbb6lp4S++0JjsT0pCAplyIX/+Z6mpnjiRV7p3J/79VassMhdoFtDxvqF+I1gVTBPLNMusMKP06flJGzZswIUBJphgggkmmGCCCdPvvaa/lbYVudufpJ8sRoRXeH8gfmASoEGDruXL9yf53W4tWjw+e5bPfHrn7ks+/5CV12ie2Ix169ZsZK61ayXzXVKVLk2+/Ikse+JEqkqVIniyIFhk8lY9LVUtiwhFaOKEfMIKc9q0adz0azQaXBhgggkmmGCCCSaYMP3ea/rfvPomudtvpG8sRmSkeiRLW6kxTVvZrJm2ZMkfye+Oqlv30T//8JnJFy4E+6wgK79+fYLNWFerxpL079+vNd8lbbNm5MsfHjzo9hNJe0hk1csvp8c8KB+k4y0vlKf/FYQK1pnR0dHssadbN1wYYIIJJphgggkmmDD9Xm36x90cRwY3Woy2GJHB4mDesdUkQEWLKitXjmGpe6pWfRgfz2cmxcV96DOCrPzo0TdsxrpAAWb6L16UzXdJ7tiRrPntzz5z+4m8t3w5ka+++WZ6zMvyZTpef4U//Y9QRVhnjtIPykv/cWGACSaYYIIJJphgwvR7temfc2eOSY9VY/VW96ZvYzQxxgG6epWl5A8MZKl71pYpk3TgAJ+fsGHDOp8mLKtPA8l6oM+eZUn6ixQRLAZdatKErDnLsVO9+u1p05IVCnedyGsDBrBBABYtslI4eMMe+puumW6dGRsbS46f/uPCABNMMMEEE0wwwYTp92rTvy6BDb/VVdXVYkS6qLvQt0s1S40DFBeXxAbfDepDpj+uUKHEPXv4/LsxMWd88vn7XvLzU1y+LFsJ9N69WiLUrKm0GPT7330nNW2qLF6cW3/60zZvfnfxYvnMGRdPpBgQQLRHJ05YKRyvKl/lW92j3YMLA0wwwQQTTDDBBBOmPzuY/rikODK4TZRNLEYkVBVK366R1hgHaOnSe35+54KDQ8JCQi7myvVg2zY+/+bHH5NbDqzwF1nmTZu0VgK9ahUbmSssTGUt6E+fJv7yy7UBA5SFCnHrL+TOrQoLk775RicITpzIJ1otQZQvvfQsJcVK4WihbEEby6PIo5E1uDDABBNMMMEEE0wwYfqzg+m/nMxasVdSVrIYkeaq5vTtFmmLcYDGjbtZuPDe4ODgAWFhZKMTNm7k868NHEgfR4bHkUUfP160EugZM9jIXAMHqu0JempiYsL69bpOncj0p7n/ggXVPXtKNFOS7D+RCRs2sGG/OnSwXjiCVEG0jarKqrgwwAQTTDDBBBNMMGH6s4npT0xNJI+bV5HXYkTqKevRt7u1u40D1KGD7uWXV5Hpn6zvcXv///4vLdDt2tHHtZMOkjMPDlZZCfTIkWxkrkmTNA4FXT5zRpwxQ9mwoaHZj1CsmLJePXHqVPnkSZsn8saoUax/8MyZ1gtHE1UT9upD1QQXBphgggkmmGCCCSZMfzYx/aQiCtZ19ax81jwiryhfoa9+1/5uHKCAALFatc/J9K/o2ZNs9L3ly/l8Tb169FH960ky5IULC9r0G/h07cqS9C9eLDl3IrVHjohRUULVqgb3zx4AypdXd+kiRkdrt21LTUw0X11Tt655JlDzfZslziLHT/9xYYAJJphgggkmmGDC9Gcf08+7ru7T7jOPCM9Yf0w+ZgjQw4epvr6KwMDhZPr36tvzGJLh8EG1nup09FRAPnzfvnT78jZsqKQFtm7VungiNfPmKevXVwYGCoULv/AAkDu3VL/+9eHD73//PRs7LCUl5c4dha+vkDdv6qNHKMRgggkmmGCCCSaYYOY40x+kZK3Yf5B+MI9IMaGY8UsAWvjUqcf61D2dyPRfHjuWHPaduXMZ5elTctX0RxP9+l2lZWbN0qQX6LJlWZL+v/6S3XYiZVkbFyfFxKgHDFDWqWNo/c//lEWK0DMATWjq1kUhBhNMMMEEE0wwwQQzJ5p+nox/vjTfPCJ5FXnpK5VOZQjQpk0JefP+TY6/a9eutyZNYq3kZ8xgnl+nY4PdlilD0998c4/M9htvqC1GWaOR6enAz09BEx46kalJSQ8PHaKnkau9eqkrVXqe+rNFCxRiMMEEE0wwwQQTTDBzoukfK44lRxwlRpmEQ9JJNN9X4WscoGnTbhcvvpVM/7hx425PnUpO+lZ0NM1/dPw4q0qvV8/wNqBSJaXFKP/1FxuZ6+WXhQw7kU+vXLn95Zfk+A3dD1CIwQQTTDDBBBNMMMHMWaZ/pjiTzP0A9QCTcFySL9H8QkIh4wC99dbVSpUWkelftGjRndmzyejf/Ogjmp+4cydLiNmuHU2npDwrXJg14DlxwkKz/q1b2chcjRopUeDABBNMMMEEE0wwwYTpzyDT/730PZn7cFW4SThOyidpfmmhtHGAGjSQatb8mEz/rl277i5YQEb/xnvvPdMPo0vT1wYN4szWrVl+nmXLLDTrX7yYjcwVEaFCgQMTTDDBBBNMMMEEM8eZfp//ZNHBW/nWRdO/S7uLzH1dZV2TcMRr42l+FWUVw5zU1GcFCyobN+5Hpv/8+fP3liwho389MpIgt2fMYLX+EyZw5vjxLIHPsGEWhuiaOJF9NXKkGgUOTDDBBBNMMMEEE8wcWtOfnul31Mrbv+Rx+bhJjT7XPnkfza8p1DTMkaQnvr4XW7cODQkJefTo0f3vv2e1+4MHE+TGmDEsfeeCBZy5aRNrwxMYaKFZ/4ABavpqxgwNChyYYIIJJphgggkmmDD9lufY6ebtN/2STvLVp9vUyC+0xonVxpLpb6hsaJizd29SoUIHgoOD+/fvTysm/PADGf2rffvS9NVevWg6YcMGzrx8WfbzU/j7C0oz2x8aylr+rFolocCBCSaYYIIJJphgggnT75Lp3+GIil8oTv5+1Z5VxjOnH5hOM+ufqm+YExn5R5kya8j0Dxs2jD7+rk/ZeaJFC5r+t1Ytmt4/e7Zh4apVz5K5nz17v8m2Kldm87/6au8OCIIgCIIgCMpG8uqafnrcqaesR/5+h7TD+BlopbSSZrZTtTPMGTXqRtWqs8n0r169mlZM3LGDZezp1ImmxWrVaDr54kUDc/Bg1oxn4kTTZv1FirDEPufO4SkTTDDBBBNMMMEEE0zU9Geg6W+rakv+/jvpO+NwfC19TTO7q7obtcyR69YdRab/8OHDtGLS3r1k9OWwMJpWFipE0yn37hmYS5awLD1hYSpj5sWLLEl/gQICChyYYIIJJphgggkmmDD9GWr6B6oHkr+foZlhHI45mjk0s5+6n2FO+fLqFi26kennwXp46BAb5rZVq5QHD2hCyJ/fmPn338zfFy2qkI2S9e/fzzr4vvKKEgUOTDDBBBNMMMEEE0yYfsszPZG9h478Y/Fj8vdjxDHG4ZiqmUozh6qH8o+XL8v+/ifJ8Xfs2DE1NZVWfPTXX+T1pcaNky9fpgkxIMAk6C+/zFryxMVpDcw1a1j1f3CwCgUOTDDBBBNMMMEEE8ycaPp9XpSJg/dcnn468hgphvx9L3Uv43DwJ4H3xPf4xz17tMWK7SDTP2rUKL7i41OnyOtr6tZNq/Jv3twk6F27skQ9c+c+Two0e7aG5rz1lhoFDkwwwQQTTDDBBBPMnFvT7zauI6Z/vbSe/P3ryteNwzFGHEMzJ4oT+cfFi6UKFZaQ6Z8/fz5fMfnCBVbBX716wubNNHGlRw+ToE+fzix+797PLf6YMWxkrqgoEQUOTDDBBBNMMMEEE0yY/gw1/fu1+8nfv6J8xTgc76rfpZmfaz7nH99/X6xRYzKZ/m3btvEVn6jV5PXVlSvfXbSIJm6MHGkS9F9+YS34AwKed9vt0YPV/S9YoEGBAxNMMMEEE0wwwQQTpj9DTf953Xny94WFwsbh6KvuSzPnaebxj507qxs2HEim//Tp03zFp1eukNdXlS1765NPaOL2tGkmQZckXYECrFn/6dNpnXmbNlXSx82bJRQ4MMEEE0wwwQQTTDBh+jPU9JPyKfKRxVfICkM4IlQRNGeJtIR/rFlTERQUTqY/MTGRr5hy+zZ5fWWxYtfeeYcm7i1bZh70Vq1Y1f7KlWkuv2JF9gwQH69FgQMTTDDBBBNMMMEEE6Y/o01/FWUVsviH5cOGcISrwmnOamk1TWu1updeOkSO/803+xhWTE1M5Jk6dR070kRibKx50MeNY434R44UOSR3biFXLoVajQIHJphgggkmmGCCCSZMf4ab/qbKpmTxf5R+fF5Jr2pFczZJm2j6yBFt6dIbyPRPmjTp+ZopKeT1Fb6+UoMGNPHo2DHzoK9bx3J0NmrEEvMfP84y95cuLaDAgQkmmGCCCSaYYIIJ058Jpp835lksLTaEo4GqAc3ZIe3Q6fPrBwTMIdP/3XffGa8r5M7N+vKWK0f/n0iSedAvXJB9fRV58rDa/dhY1q83MFCJAgcmmGCCCSaYYIIJJkx/Jpj+SDGSLP5kcbIhHDWUNWjOfu1+mv7sM/G1194j03/gwAHjdZUFC7IWPmT9c+VKTU62GPSaNVnn3Z9/1n77Lav179RJhQIHJphgggkmmGCCCSZMfyaY/s/Ez8jiD1EPMYSjkrISzflT+ydN9+unbtbsDTL9Go3mBdNfvDhr4ePjoypRIr2gDxigpkUm0/PEZNa+f9gwEQUOTDDBBBNMMMEEE0yY/kww/d9K35J576LuYghHSaEkzflX/pemmzc/R44/PLxdSkqK8bq8YQ8bl7dOnfSCvmgRG6KrXTvV4MHM/U+dqkGBAxNMMMEEE0wwwQQTpj8TTP9W7VYy742UjQzhKCAUMCTxrFRpD5n+wYOHmawrBgRw0y+HhaUX9CNHWFP+EiUE8v00sWKFhAIHJphgggkmmGCCCSZMfyaY/iPaI2TeKwoV+UdZJ+dS5KI/mjh/Xle+/Aoy/V988YWp6a9Rg5v+a/37Wwl66dIsPf+rr7LG/bt3a1HgwAQTTDDBBBNMMMGE6c8E06/Sqci8+yv8yeXTR0En0Mf8ivw0HRurffXVz8j0b9682WRdTb163PTfHD/eStA7dWJ1/AULMuv/778yChyYYIIJJphgggkmmDD9mWD6SUUVRcm/n5ZP0zT9p+kSQgmajomRGjR4l0z/8ePHTdbVNm3KTf+duXOtBH3KFFG/lCJvXoUso8CBCSaYYIIJJphgggnTn0mmn+fo/E3+jaaPykcNrX1GjlS9/np7Mv137941WVcOCuKmP+GHH6wEfccOiZv+KlUEFDgwwQQTTDDBBBNMMGH6M830B6uCyZmvkdbQ9AHtAZqurqxO023b/kWOv0OHbubryuHh3PQn7dtnJeiiKOfJwxZs2lSFAgcmmGCCCSaYYIIJJkx/ppn+3qre5N/naubS9E7tTpoOVAbSdJ06W8j0v/vuGAvrdu7MTf/js2etB/1//2O9eF9/XYkCByaYYIIJJphgggkmTH+mmf73xffJv38ofkjTm6XNNN1S1VIU5YCABfrUPfPM173asyc3/Sm3blkPeuPGzPQ3aQLTDyaYYIIJJphgggkmTH/mmf7Zmtnk3/ur+9P0amk1TYerwg8elGvX/pBM/6ZNmyyY/j59yPELuXPbDPqsWRpy/PQfBQ5MMMEEE0wwwQQTTJj+TDP9q6RVZPTDVGG6/wbo7arq+v33UpMmvcn0Hz161ILpf/NNMv3K4sVROMAEE0wwwQQTTDDBhOnPAqZ/j3YPGf06yjo0PV+aT9N9VH0mTlS0bh0SEhKq0WjM173SoweZfnWVKigcYIIJJphgggkmmGDC9GcB039CPkFGv6RQkqana6bT9Dvqd3r02B8cHNyly9sWA3Sla1cy/ZratVE4wAQTTDDBBBNMMMGE6c8Cpl+r0/op/HIpcomyOEkziUz/aPXoZs1Wk+kfPnySxQDp2rUj069t0gSFA0wwwQQTTDDBBBNMmP4sYPpJZYWy5PWPycd4Jp+PxI9q1fqcTH9MzFKLAdK2bk2mXw4ORuEAE0wwwQQTTDDBBBOmP2uY/kBlIHn9WG3sMHEYTYw/O6V+/eFk+nfv3m0xQHcWLiTHT/9ROMAEE0wwwQQTTDDBhOnPGqa/vao9ef3l0vL+6v40ERk3u2XLTmT6z507h8IBJphgggkmmGCCCSZMf3Yw/YPFweT1P9d83kPVgyZ6f/cFOf6QkM4oHGCCCSaYYIIJJphgwvRnE9M/QZxAXn+UehSv8g+LmkKmPyJiJAoHmGCCCSaYYIIJJpgw/dnE9C/QLCCv/4b6jSBlEE006xNFpn/EiFkoHGCCCSaYYIIJJphgwvRnE9O/UbuRvH4rVatGykY0ERg6jEz/woXrUDjABBNMMMEEE0wwwYTpzyamP04bR16/qlC1llCLJhq36kmmPy7uIAoHmGCCCSaYYIIJJpgw/VnA9N+5c2fKlCn030qALsgXyOsXEgpVEar4XvRtHRzaunWIWq1G4QATTDDBBBNMMMEEE6Y/C5h+cvzBwcH9+/e/du2alQDlV+Qn319KUarQgUL61D29UTjABBNMMMEEE0wwwYTpzzI1/UOHDiUf36tXL1EU0wtQgBBApr+gULDMmjK0cNeuUSgcYIIJJphgggkmmGDC9GcN009KTEwcO3asPgtnxIULFywGqLmqOZl+X4Vv1dlVacnIyK9QOMAEE0wwwQQTTDDBhOnPGqb/ypWnffpcFcXEiRMnkpvv2LHjiRMnzAPUXdWdTD/91R1ZnxZbsGA7CgeYYIIJJphgggkmmDD9WcP0k+MnL1+ypGrbtnvTp08nQ9+2bdvDhw+bRGGEOIKb/hZdW9Eyhw6dROEAE0wwwQQTTDDBBBOmP8vU9Ldtq/PRO/oRI67Nm7eQPH1oaOjGjRuNozBVM5UW8T/pT98GBbWXZRmFA0wwwQQTTDDBBBNMmP6sYfpJqanP5s+/kzevQL6/Vi3NrFnL9fl5Qr7//ntDFJZqlpLpL7ajmN70D0HhABNMMMEEE0wwwQQTpj8rmX6ukycfk+Mn30/uf/ToNWT6yd9/9VVah93t2u1k+issqUAzO3eeisIBJphgggkmmGCCCSZMf9Yz/aSkpNSRI2/wpj7BwT+0aRNKFn/mzJmyLB+Vj9LsGpNr0JyhQ79H4QATTDDBBBNMMMEEE6Y/S5p+rp9/flCqlIp8f5UqW0JDw8nlf/LJJ4IkkOlvOLAhfZw3bx8KB5hgggkmmGCCCSaYMP1Z2PQ/0/fubd2a+f6iRXe2adOejP64ceNeOvNSUHgQTcfFXUbhABNMMMEEE0wwwQQTpt+dpt/HSBlj+kmyrJsyRcyTR1G48G9BQZ3J6zcb2Iz97xys1aJwgAkmmGCCCSaYYIIJ0+9u0++oZXfd9POD/+03+dVXlQUKHGrRonuwXoFvB6NwgAkmmGCCCSaYYIIJ0+9O029i0130/Y6afpJSqRs0SMyX76+W7VnbnmZvwPSDCSaYYIIJJphgggnT78Wmf4ezio6OK/lF88Z9G5ed13wHBEEQBEEQBEH2KRNMvysaemhOwW3N6P8zCIIgCIIgCIK8tqYfgiAIgiAIgiCYfgiCIAiCIAiCMtb0P3Nr9h4IgiAIgiAIgrzU9LsrTz8EQRAEQRAEQd5o+j21DUceJOx/8HD0EcXmkj4vyi3H5WOmjDx2K8vYJLiyrjds3eaS1gkW13WohKS3pD0E61t38TpyceuOXiCunDv3Xu8ZsHWbIbKnzLtS6tI7v05fs45WAzld6qxv3aFCawXi9nW9Yeu412X6vc71Xy43/ho6vfPuvaKdOCKb8z16RFn3HHmd6TccpEPL2CxPTsBt3ridOxyHfhFdPyLjA3E0qi7G2YnIu0JI7+K3Z9M2j9H6Bex0tG0eo02a9fg4ccbTK6vp3aHs2ZwTV5z9pc76uq5v3Z7C41wZcOJxwi2htv9c23m5OdfFy56SZudF52IoLB6v/U9NrgTBRYLxus6VOqfvdc+cauJrZT/tuddZWcbRy9zO+56j17UTnsz6rdWJBzOHmJ4wkU5ckk47LudKgutH5IpncJSZia1pvMv0u36Lt76Au0y/cyfMxRu3G223048iblnARdPvllNmT3lw5YfQEybA9evI7b9erlxxNr9yvVg652JdX9e543Kj03WiCLl+b3Tx+TBjfg48ejN0/dnJLaXOoXudW0y/0/c6z1VwuOvW6q7felfOkaNMbzD9rjiuzDL9rnsG+5kw/Z514fbXl9j/MveZUy++Yfq9wfQ7euGZ1L05987Xe0y/o6/OPXRrs3nHd9FbO2ehXFnXegmxs9bTlRfB6Z1f+82Nldfr9j/mWdy6zSYudi4D0+/QLcLp94qOljrvNP0OlajMMv1Ov0V0/dx5yPS7+F7U0817XLkY3Wj60bzHybofO1scOvGzYX8DGzdWZdnfftT+rbtSTJ1owWbnTcGJnxPnIu/e2iA7S0h6UXLCPrpifaw3U3Fi688cb6LgtLVyrl24ddthTztUi3d850qd04+arjTOtjht5yWZ3lacaGhhc9qh6zoTHb+LD8kOtYx3+l7n9KPmM7t7HaDUZRXT7+jvlPeb/ow8Ilc8gytuKqebfjc+ITjd1s3tPQqcM6Y2PZkb665smlS3/I7arJ+w/zfYvQ3cHf3VcWMbX/tNthub9zixdRdrK22WOjvLnhPXuz3Hbn15h0qd9UcIVx6unLgvOXrszzzZ0MKJrT/zTBsnT1zvdobRzq3bWersiXx6pc4tfXgsAu08did2JmO2njGm3/47g9PvvTPY9LtyRO5yHZ4zeM4dkRu9RPY0/e5tCOR0T/yMbGDzzH2t1d31PJ3xpj/Dtm5/PhC3F2mvatPvoa1bj7Bbsl05cb3bXyvmytatRN6JJDyeNv1OuFU3mn73bj0n3+vsbObh6Y77OfBe58aqLid+j7zW9Lv4C5u5pj/rHlFWNf0uNthwBe5odhE7l3T7HcfRdxeuNFX0wuw9Hv2Rtj9oTmeX8pLsPc6ZABdfwbkrQVYmtq52/R7iSs4op+9LDvWUcK6hhZ1bt6c3hXtNf7a/17nSNt3OGmgXkz45l7LJiYx/Dv1Gu75158qh069T7GQ6kbHKQ4/TnujI69Ej8kRjaRe9RJY0/c4lqndjVnuHzqjbRwlwohG2E43FHYq8nTVArmRfdpFgz7oOHbujP4Sey5zteu7qTNn6M5dfwTla2+1inn4XCc6VOjvLtifOGkqdJ97euH6fd7GCMGuVOueO3fqmM37rz1xr2OPKr567mJ7Iau/EncGNSQsy/ohc8Qzu9RJZz/RDEARBEARBEJSJgumHIAiCIAiCIJh+CIIgCIIgCIJg+iEIgiAIgiAIgumHIAiCIAiCIAimH4IgCIIgCIIgmH4IgiAIgiAIgmD6IQiCIAiCIAiC6YcgCIIgCIIgmH4IgiAIgiAIgmD6IQiCICidnxar49VbX8YKM4OHrIcgCILphyAIgq99QS6aYxOCW9xtJlpkK6bfld2D6YcgCILphyAIykxf66IfzWZ2FqYfgiAIph+CICibm/703gCYz+TT5svbpJmsaH0P7V/YZB+sH4WV+Ra3Yufy1jnw/RAEQTD9EARBmW/6zX2zRR+f3oT9NJu15o4ubO68rR+FPftp0/Q7dJgw/RAEQTD9EARBGW36rdTBW/H39nzr9HzXF7Z/FQ9twrk9gSAIgmD6IQiCPGL67ZlvseFKljD9DjW/gemHIAiC6YcgCILpt2HHvbym30WnDtMPQRAE0w9BEJTdTH/GtOn3tOm3+UbC/ob4FrfiRJt+OH4IgiCYfgiCIK8w/c8cz95j/pWd2Xs8Z/rtPAr7s+5YPy47OTD9EARBMP0QBEFQFnhSsmnc7XmFAkEQBMH0QxAEQVn7wQBBgCAIgumHIAiCYPohCIIgmH4IgiAIgiAIgmD6IQiCIAiCICjn6P8B4gXOMzGthSwAAAAASUVORK5C" alt="Per base sequence content" width="1020" height="600"/></p></div><div class="module"><h2 id="M5"><img src="data:image/png;base64,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" alt="[FAIL]"/>Per sequence GC content</h2><p><img class="indented" src="data:image/png;base64,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" alt="Per sequence GC content graph" width="800" height="600"/></p></div><div class="module"><h2 id="M6"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAFlUlEQVR42s2XCUzTVxzHybIs0IgCLYqyQ9RtmhjCNKKbikajYVc22NThNjYjeC0yWBESxAV1Ckw8QEUF5ChnS4FyFETucwWU+7ClHKKiImLI4nCz9bv3/pS7ra1HtM1Lm/b/fp/ve+93PQMABq9y6D/Bz+ANNvethWxPw3Xs3wx/YAb9Tn6j/700AeZc1qccrhGPw2UNkk8Fx9voIceX9Tcz6Hf62/B/PPrsCxNgzjW043iyGjheRkOWQRzFt2IH/Nl4DDFyHjJ6siDoSoZ/YwB2VuyEffpGzA5iK+izdA6d+8wCyHa+SYyEsj2N/jU/aaL0vbIf0sF2tA92oOVBG+ruN6CqrwZldypR0FuMnBuXkX49C5GyaGwq3ASLU2ZKOpfaoLb0EmDibmLC8TQq5/iw/vlIaA1xjxiyQTmaH7Sitr8ekr5qlN6pQP6tImTfyIXoeiYEnSmIlSfiooyHc20R8G84htUZq0FtUFvUpk4ChldO4H6sRzvKXdEw0ISmgRZc7a/DXwRccrscebcKIb5xCWndGeB3CsGTJyBCGoPQtnCcajlLjugk/qgPxO+1h7Eqyw7UFrWpbiemCKBbRlW7lrmgcaAZV/prUXm3CsW3y3D5VgGyenKQ2p2OpM5k8NoTEC6Nxtm2MJxsPoPAxhM4XB+AA1cPwbvmADyqvPFLpQdsM1aodoIVqlUAdRp6bgv5HzBbXHFXgqLbpci9mY/MnmykdIuQ2CFATHs8wqRRONN6ASeaTyOg8TgO1fnDl4C9anzhLvHCnkp3uJTvgXOJC7YUOWN+0nww/jTJMSevvsHs+DRlSOsZFPaW4NLNPOLpYgi70pBAwFHtcbhwLRKnW8/jeHMIOecgHKw7iv1XD2Jf9X78KtmHyNZoiOQi/FiyHZsJ+Ov87/DZZUesEq8H+4SxkjLUCmDinISPY74jcm4Oe3RyVyriO/iIksUS8EWEtJ5DUFMwjhIH86s7Ap8rfvCs9oGbxBO7KtwQ3hKBrgdd6H94D3ypgIAdsD7nc6wWb8DyzDWYy58HyhifJ8ZWT5NMoLGCJ48jsZ2COHkSCSkezl+LQHBLKI40BGJLsRPW5qzDskxbLE5bDBuRDWwzV5DV2SGwNhCdAx0Yed172AdeWyyWpa/ColQbzE1+H7MTLcEOmKagrAkCaAqlWWwZf6kqlMY8+gDZ3jXZazEz0Rym8TPUDg+yetl9Kca/HikeIUUmgEXizAnPml2YDsoaSduMAJrHaSrdWvw9AYcR8LBHu0m4eJtvqRGsDS4k8DlJFlPnxM0AZVHmmABSTGg+31GxW+XRAfi51AWztKxaI/zxELNytXDVoCzKHBNAKhotKrsr9zIe7Vq+G5wEs9EJi1I+hFDKx7zkuTrAk7XCGQGERZlTBLiSuN1Ltn2BcMEEeGF3PoaI8dzObFgJ3nsuuHoBqiNwLNgMu+x1ow9SByrsyoNC+ZiBPFb8h5LrhWrhqTKhTnD1R6BywuWZn0zYejq2FTuj/k7tKEz5RPlccLVOOBKG7DATtZO+yXNATW81npD3ZHhaux5wTWE4kohoktA0cWPOelT3SkZFDMNT9ICbwCJplvpEND4Vm8ZqNrJBJWJIT7h5Ioek5a+wRLRUcyoeX4y0GaMiaEjqCn9X8A62le0ADXGLYLbmYjS+HJtGTdf5TLUNa5E1Kc8+8K09iPkJVk8vx+MbEm1H8bTBTjDFF3lfMlmVNipLREt0a0gmt2TPIsKKZEv3Ki5TU2gZt8+1168lm9yU6noc1MO3FDkxYNojhpH+YW2Gnf5Nqbq2nHHMWPVbbZNuA6firQghpZt2TRHSSGwn/eScYPNnb8s1XUxoDFtGWpD6sAgrxSvhSi4juypJ31f6ExwLSNsl/BicAOMXczF5ba5mr83l9GWN/wE1f784zfWjGwAAAABJRU5ErkJg" alt="[OK]"/>Per base N content</h2><p><img class="indented" 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" alt="N content graph" width="1020" height="600"/></p></div><div class="module"><h2 id="M7"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAEpklEQVR42s1XfUyUdRz/URrktNpaW/aHW1LLNdN0+U9WSzdfcq31/uLrWvZP+Y/2T+mc54GplSCOt4CBgqicpICGwokvSYkc3B3nQJxmBSo0K6fsiJe759Pn+zzccRx3xyGwvO07fvye5/f9fH7f90cBUP+nDP+QSd1XZ1LT6hPU/FqzWi4ia9mTZ2NGwLZZvUag/Dqzul2XoDzOROVu3KI6RGQte/JM3pF3R41AbaJ6pT5RNdgT1L+tyXGezpJFgM0MNGYDV34ALhUAtZugWZeh0/IiWpNiPfKunJGzd03glEmNo6L0erPqbkse59WqvwD+bgJuXQL+cgF/2oAbPwPXTgJ/HAOulgKXLYArHdqRxWjfGeuVs6JDdA2LgMOkHrGbVbVri+rsyZ9K5YeBfy4CNxsIXEvgaqC1Cvi9nM9KCFwENNMSjTk6ATiSgfMb0XtgJkSH6BKdURHQb84DzVtVl5gVN+0UJ9B+Hrh+lsAnjBsL+K8Ev3KQbtgLXMgkcBJQt5Xgm4Fz6wFaTds/A6JLdIayxCACYjJhrVV+RGAHgWsI/BPQYgV+O0rQQ1xXAJ4uwNvNv5TeTuBiHoFNwC9fAWfXAWfWACc/BayroBVOMyxB3REJ6AFHv/XkTuZN6dvrpwlWSeAjfQG3j0C7DRKaB/6frF2pBF4LnP4cqFpN4JXA8Q+AH98CypagN+dRiO7gwBxAQCK3bYfywv4NzcxbXi0jcDGBC4GmPMPMDSmGv4MJ1G8n8CdA5XLg2PsEfpPAzMbD84Hil4B9z6E9KcYrGCEJSO5K+mhlC/oimr5tpm+bcgmcATh3EoTEbAnG/4EEvL1AzUYCvwccfQMoXUzgeQSeCxS9oIOj4BloWQ9DMALrRP/tWUBavovx6PkdGNHOZON25zZQ+RLAMpumfYegPQEEuLby5haCWeYYoPtnAoXPAvlPAbmPAwRHZixavlUewRpIQMorq5h7z9NGgXGl9UX0Nj2SYZnFw+OBdGVI8Rwj+Hw/Wcue73kEuZOiIFi+sq0TkDoupRTlNJ9jR18qmQyfZk8crGgEBDSKXrald/gISDOReo7KpQTexFT6kv58l7d+ILSiERAQESzB9BOQjiZNBdYVRipVsAZk3B9eyQgJCJZgDiYgwFUfM2gei6xktAn4XVDCFCx6fmglo+0CfxCyZEY0/VgFoS8N7+yKie4WAtZ1iz3AbYisR5KG/kLEIhEVgawJLDLxA0X2hjqXGRemEAWUYm9adH7Ui9PlA4bIOtK7GezCRS9D2xMfvhQPaEbRWKCjpT8GZB3OAlmT2JRYU8pXGFNSuGYU2I67U4cgUPrq4G4oe8Hv7Z4CnPiMLXoderKjaMeBA0lEV+Q8BLjb+gnIWvb8Jmd8FROnmlW15mt4C+KjG0iCR7KIJKRty8AiIms/OY5+Vk5CNvYURwY0tuRhjWTBQ+mQ7vDJ93H65AMbu2gDO6p9F4fS2cMfSkOO5QzMkNYQU+c/SeDX+W3AmeECpyZnKrTjH6I95cG7H8vDfZhIDnekTYCW9wSnnOnsmOyeFWxg5W9DK10I997pzPOY0fkwuWc+ze6Zj9Oxkv8AsrpUzUM9ceYAAAAASUVORK5C" alt="[WARN]"/>Sequence Length Distribution</h2><p><img class="indented" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAyAAAAJYCAIAAAAVFBUnAABElUlEQVR42u3dB5hcZd3w4RQCoQcQI0WJIE06MdRI6FWQoBKKSvOlKbxSBKIiUgRRlCIKCFIMiBIQJCCSl/ZRAgiGJk2m7LRN771tvucYxJDszs7sPrvZ2b3/Vy6usMnM3nvKzC/nzMzpttgYY4wxxkSdbhaBMcYYY4zAMsYYY4wRWMYYY4wxAssYY4wxxggsY4wxxhiBZYwxxhgjsIwxxhhjjMAyxhhjjBFYxhhjjDECyxhjjDHGCCxjjDHGGIFljDHGGCOwjDHGGGMEljHGGGOMEVjGGGOMMQLLGGOMMUZgGWOMMcYYgWWMMcYYI7CMMcYYYwSWMabsHtWtWwfndXBhh13ytbXcPtJ21tVtjMAypiMWxkdT+TNohX9a7fNZVYYulQgr/Kdrz1UjsIwRWMZ0qqfhyp9+KvybrQys2koQgSWwjDECy5jGn28afSpa5hDX8ge9lvzmo680+jeXucPlv2lTd9vUN13+hmV+zGZ/hEb/fvk7KfMzlsmRan+QqjBxv+PSK7TMGq8E3OzqaGojLC+v5M4rCazaXePNLm1jBJYxHTSwKnmiKvN81tTvKznAUMn9lOm2qgxNPTVWDqi8GCr/QRq9zzI3jP4dW7DGW7A6ygR35T9yJdtV+WVVc2u82aVtjMAypjYCq9lnssqDqU2/3gJblDtp66+34Kdun0Vd+Tm4yhuoxd+ilRtzDa1xUWUEljE1HFiLGzsN0YkDq6mft6oTQ5Wc82rB/ZS/k7b4jtUG1uLmTlpVFViVyMsvnMqrukbXuFOERmAZU8OBFet4Rq0EVosPd7X46EtrjmesEHkLlnwrj2BV8uO37BRhJ1vjxggsYzpcYFX+qprKA6uS14605oUslTyjx30NVit/wKqWZ7OvyKkkhVvzHVuT1FWtjkr+t6rAqvwIVu2uca/BMgLLmI4bWJV8DlazJyYqPD/S6Ldu9O+XMVR+prKq2zZlK38ni8u+U7LRF3FX+4O06bsIm/37layaxdWcImx2SbZmxZXZrircQmpujTtFaASWMaZLBKufyBo3xggsY4yn2yZ/CodGBJYxAssY4+k25g+irgSWMQLLGGOMMUZgGWOMMcYILGOMMcYYI7CMMcYYYwSWMcYYY4zAMsYYY4wxAssYY4wxnXlmP/PMpEsuCf/t0oHVFp+hUt8G0xY/OycnJycnZzs7nzFtOQLLjsfJycnJ2UUDyyGuNhqBZcfj5OTk5BRYRmDZ8Tg5OTk5OQWWwBJYnJycnJycAktgNRJY5a912uifdltqKvm6wOLk5OTk5BRYXfEIVqMBtPQXG/398oHV1L0JLE5OTk5OToElsBaXOaZVSVSV/187HicnJycnp8DquoG1/Cm/lgXWI8YYY4xprxFYHTqwlo6nak8LOoLFycnJycnpCJbA6tbKU4ECi5OTk5OTU2B1gkmVjRaBZcfj5OTk5BRYHxbDR786a/dEvOe2Daxl4sm7CDk5OTk5OWsxsKqqB4EVLbC6fXyWqSKfg8XJycnJydmZAquSI1tLf/2jPypTIY3ez5Lfl7//qg6zNfr1Fn/rj/6oqZ+0KYxPcrfjcXJycnIKrMVlemXppKjk943mTiW3LfP3m71hmR+kld+6zI/W6M0Flh2Pk5OTk1NgVXSYp9EKac+vV36SrtHAalOqwLLjcXJycnJyVhQByxzCqfxUYPkjWC2+n/J3UskRrCg/gsCy43FycnJycsYJrPJ/oTVHpFp5BKuSO2y7H0Fg2fE4OTk5OTmbCaxKXju1uMoXKlX4gqdmv2+zd1LJEawWf2uBZcfj5OTk5ORs+RGsSt4tWObU2/JfX1zxuwgb/d8Wv4uw0bOBLfvWjd6JwLLjcXJycnJytuQUYbVT059N2hY/msCy43FycnJyCiyBtbjZ04UCy47HycnJyckpsFr7E7XmqkECy47HycnJydl1A8u03QgsOx4nJycnJ2dncxYffzzVrVtmm21WrFNg2aA5OTk5OTk7UWD96U9JYA0cKLAEFicnJycnJ2ccZ/7mm0Ng1R1+uMASWJycnJycnJyRAuunP00C6xvfEFgCi5OTk5OTkzOOM3fRRSGwcmedJbAEFicnJycnJ2ekwDr99CSwLr5YYAksTk5OTk5OzjjO7JAhIbAKv/ylwBJYnJycnJycnJEC66CDksC6/XaBJbA4OTk5OTk54zgzu+6aBNaf/yywBBYnJycnJydnpMDacssQWMWnnhJYAouTk5OTk5MzjjPdt28IrNJrrwksgcXJycnJyckZx5laeeUQWPXZrMASWJycnJycnJwxnOl0qKtU794r3CmwbNCcnJycnJydxFn6xz9CYKU/9SmBJbA4OTk5OTk5IwXWE08kV3reemuBJbA4OTk5OTk54zgLw4eHwMruvrvAElicnJycnJyckQLr1luTwDrkEIElsDg5OTk5OTnjOPM//3kIrLpjjxVYAouTk5OTk5MzUmD94AfJlZ7PPFNgCSxOTk5OTk7OOM66M88MgRUyS2AJLE5OTk5OTs5IgXXccUlg/fznAktgcXJycnJycsZxZg89NLnS8623CiyBxcnJycnJyRkpsPbYIwms4cMFlsDi5OTk5OTkjONMb711cqXnJ54QWAKLk5OTk5OTM1JgbbBBElivviqwBBYnJycnJydnHGdq1VWTwEqlBJbA4uTk5OTk5IzhrKsLdZXq1asjOAWWDZqTk5OTk7MzOEuvvRYCK/3JTwosgcXJycnJyckZx1l8+ukQWJktthBYAouTk5OTk5MzUmA9+GASWLvsIrAEFicnJycnJ2ccZ+GOO0JgZQ88UGAJLE5OTk5OTs5IgXXttSGw6oYMEVgCi5OTk5OTkzOOM3fxxSGwcqedJrAEFicnJycnJ2ekwDrrrCSwLrxQYAksTk5OTk5OzjjOum98IwRW/qqrBJbA4uTk5OTk5IwUWIcfnlzp+eabBZbA4uTk5OTk5IzjzAwcGAKr+Mc/CiyBxcnJycnJyRkpsLbdNgmsxx8XWAKLk5OTk5OTM44zvfHGyZWeX35ZYAksTk5OTk5OzkiBtcYaSWC9/77AElicnJycnJycEZylXC650vNKK3UQp8CyQXNycnJyctZ+YL35ZhJY660nsAQWJycnJycnZ6TAevbZJLA220xgCSxOTk5OTk7OOM7iww+HwMr07y+wBBYnJycnJydnHGfhrrtCYGX33782Aqvbf6ZMGy3zp92Wmkq+LrA4OTk5OTk5W+nMX399CKy6r361lo5gVRtYjd6qqa8LLE5OTk5OTs7WBtallyaB9a1vdYbAWvL1pf+02tgSWJycnJycnJytd+bOOScEVu7882s+sBqNp5YF1iPGGGOMMa2YV7/0pRBYL5x++gqXdKDAcgSLk5OTk5OTszXO7JFHhsAq/PrXtX0Eq6moElicnJycnJycKyCwBg1KAuuee2o+sJYZgcXJycnJycm5opyZHXYIgVV89NGafw1Wi49aeRchJycnJycnZ+TA2mST5ErPo0bVRmA1epiq2cDyOVicnJycnJyc7elMrbVWCKz6d96ppSNYbf79BBYnJycnJydni53FYqp791SPHuE3AktgcXJycnJyckZwlt5+O9WtW6pPn47jFFg2aE5OTk5OzhoPrBdeCIGV7tdPYAksTk5OTk5OzjjOwiOPhMDK7LSTwBJYnJycnJycnJEC6+67Q2Bl99lHYAksTk5OTk5OzkiBdeONSWANHiywBBYnJycnJydnHGf+iitCYNWddJLAElicnJycnJyccZy5884LgZU791yBJbA4OTk5OTk54zjrTjklBFb+sssElsDi5OTk5OTkjBRYX/lKElg33CCwBBYnJycnJydnHGd2v/1CYBV+/3uBJbA4OTk5OTk5IwVW//4hsIojRggsgcXJycnJyckZx5nedNMQWKXnnhNYAouTk5OTk5MzUmCtu24SWG+9JbAEFicnJycnJ2cMZ6mU6tkzCax8XmAJLE5OTk5OTs4YzvfeS670vOaaHcopsGzQnJycnJycNewsvvhiElif/rTAElicnJycnJyckQLrscdCYGW2205gCSxOTk5OTk7OOM7CvfcmgfXFLwosgcXJycnJyckZKbBuuikEVvaIIwSWwOLk5OTk5OSM48xdeWUIrLoTThBYAouTk5OTk5MzUmBdcEEIrNz//q/AElicnJycnJyckQLr1FOTwLrkEoElsDg5OTk5OTnjOOuOPjoEVv7aawWWwOLk5OTk5OSM48wecEAIrMKddwosgcXJycnJyckZx5kZMCAEVvGhhwSWwOLk5OTk5OSMFFibb54E1jPPCCyBxcnJycnJyRnHmV5//eRKz6+/LrAEFicnJycnJ2ekwOrVKwRWfS4nsAQWJycnJycnZwRn6YMPkis9r7ZaR3MKLBs0JycnJydnzQbWK68kgbXhhgJLYHFycnJycnLGcRb/7/+SwPr85wWWwOLk5OTk5OSMFFj33Zdc6XnPPQWWwOLk5OTk5OSM48zfcksSWIcdJrAEFicnJycnJ2ekwLr66hBYdccfL7AEFicnJycnJ2ccZ27o0CSwvv1tgSWwODk5OTk5OSMF1hlnJFd6/uEPBZbA4uTk5OTk5IzjzB5zTBJYv/iFwBJYnJycnJycnJEC6+CDQ2AVfvc7gSWwODk5OTk5OSMF1m67JYH1wAMCS2BxcnJycnJyxnFmttoqBFbxyScFlsDi5OTk5OTkjONM9+0bAqs0erTAElicnJycnJyccZypVVYJgVWfyQgsgcXJycnJyckZw5nJhLoKjdUBnQLLBs3JycnJyVmTztLo0cmVnvv2FVgCi5OTk5OTkzOOs/jkkyGwMlttJbAEFicnJycnJ2ccZ+GBB5IrPe+2m8ASWJycnJycnJyRAut3v0sC6+CDBZbA4uTk5OTk5IzjzP/iF0lgHXOMwBJYnJycnJycnHGcuR/+MARW7owzBJbA4uTk5OTk5IzjrPv2t5PAGjpUYAksTk5OTk5OzkiBdfzxIbDyV18tsAQWJycnJycnZxxn9rDDksC65RaBJbA4OTk5OTk5IwXWnnsmV3q+7z6BJbA4OTk5OTk54zjTn/98ElgjR9ZeYHX7zzRaRY3+abVfF1icnJycnJycLQmsDTcMgVV65ZVaPYJVPomWaaaPfr98YFVybzZoTk5OTk5OzooCa7XVksD64IPOE1hN/YUKo6r8/9qgOTk5OTk5OZtx5nLJlZ579eqYzg4RWI8YY4wxxlQzfxs2LATWe336dDRYtMBq9PygI1icnJycnJycbecsPvNMCKzM5pt3ziNYFZaTwOLk5OTk5OSMGVgPPZQE1oABnTCwmn25usDi5OTk5OTkbAtn4c47kys9H3BAZwusZqvLuwg5OTk5OTk528iZv/baEFh1Rx9dk4HV7ePT1Neb+qNlKsrnYHFycnJycnJGceYuuSS50vOpp9bwEaw2/34Ci5OTk5OTk7OqwPrf/00C64ILBJbA4uTk5OTk5IzjrDvhhCSwrrxSYAksTk5OTk5OzjjO7BFHhMAq3HSTwBJYnJycnJycnHGcmb32SgLr3nsFlsDi5OTk5OTkjBRY220XAqv42GMCS2BxcnJycnJyxnGmP/3pJLBefFFgCSxOTk5OTk7OSIG15pohsOrfe09gCSxOTk5OTk7OCM5SPh/qKtWzZ32pJLAEFicnJycnJ2eMwHrrrRBY6XXW6bBOgWWD5uTk5OTkrLXAeu65JLA23VRgCSxOTk5OTk7OOM7iiBHJlZ779xdYAouTk5OTk5MzjrPw+98ngbXffgJLYHFycnJycnLGceZvuCEEVt1XviKwBBYnJycnJydnpMC67LIksE45RWAJLE5OTk5OTs44zty55yZXej7vPIElsDg5OTk5OTnjOOtOOikEVv6KKwSWwOLk5OTk5OSM48wOHpxc6fnGGwWWwOLk5OTk5OSMFFj77JME1t13CyyBxcnJycnJyRnHmdlppySwHnlEYAksTk5OTk5OzjjOdL9+IbBKL7wgsAQWJycnJycnZxxnqk+fJLDefltgCSxOTk5OTk7OGM5iMdWjR6p79/AbgSWwODk5OTk5OWM433031a1baq21OrJTYNmgOTk5OTk5a8lZGjUqBFZmk00ElsDi5OTk5OTkjOMsPvpoElg77CCwBBYnJycnJydnHGfhnntCYGUHDRJYAouTk5OTk5MzUmD9+tdJYH35ywJLYHFycnJycnLGceZ/8pPkSs8nnSSwBBYnJycnJydnHGfu/POTwDrnHIElsDg5OTk5OTnjOOu+9a0QWPlLLxVYAouTk5OTk5MzUmB99atJYF1/vcASWJycnJycnJxxnNn990+u9HzXXQJLYHFycnJycnLGcWb69w+BVXz4YYElsDg5OTk5OTnjONObbZZc6fnZZwWWwOLk5OTk5OSMFFjrrZcE1ptvCiyBxcnJycnJyRkpsFZaKQmsXE5gCSxOTk5OTk7OCFN6//1QV+k11ujgToFlg+bk5OTk5KydwHr55SSwNt5YYAksTk5OTk5OzjhTfPzxEFiZbbcVWAKLk5OTk5OTM1Jg/elPSWANHCiwBBYnJycnJydnnMnffHMIrLrDDxdYAouTk5OTk5MzUmBddVUSWN/4hsASWJycnJycnJxxJnfhhSGwcmedJbAEFicnJycnJ2ekwDrttCSwLr5YYAksTk5OTk5OzjhTN2RIcqXnX/5SYAksTk5OTk5OzjiTPfDAJLDuuENgCSxOTk5OTk7OOJPZZZcQWMUHHxRYAouTk5OTk5MzUmBtsUUSWE8/LbAEFicnJycnJ2ecSX/yk8mVnl97TWAJLE5OTk5OTs44k+rVKwRWfV2dwBJYnJycnJycnBFm0cyZoa5Sq67a8ZenwLJBc3JycnJy1oZzQT4fAiu9wQYCS2BxcnJycnJyxpl5r7+eBNbWWwssgcXJycnJyckZZ2Y/9VQIrOweewgsgcXJycnJyckZZ2bef38SWIceWvOB1e0/02gVNfqn1X5dYHFycnJycnJWMtN++9sQWHXHHddJjmA1FViN/mm1XxdYnJycnJycnJXMlJ/+NAmsM8/stIHVyqgq/782aE5OTk5OTs7lZ+IFF4TAyv/gBwKrosB6xBhjjDGmufnHQQeFwHr+rLM6MtIRLP9i4OTk5OTkrCXnmMGDQ2AVbr3VESyBxcnJycnJyRlnSoMGJYE1fLjAElicnJycnJyccSa/3XbJlZ6feKLTBtZi7yLk5OTk5OTkbF9n3UYbJYH16qs1H1jdPj7LVJHPweLk5OTk5ORsN2d61VWTwEqlOskRrDb/fgKLk5OTk5OTs+w0zJkT6iq18so1sTwFlg2ak5OTk5OzBpwLSqXkSs99+wosgcXJycnJyckZZ+a99VYIrMyWWwosgcXJycnJyckZZ2b/v/+XBNauuwosgcXJycnJyckZZ2Y++GAIrOxBBwksgcXJycnJyckZZ6b/7ndJYA0ZIrAEFicnJycnJ2ecmfLzn4fAyp1+usASWJycnJycnJxxZtLQoUlgXXSRwBJYnJycnJycnHFm/GmnhcDK//SnAktgcXJycnJycsaZsV/7WhJYN98ssAQWJycnJycnZ5wp7bdfCKzin/4ksAQWJycnJycnZ5wp7LRTEliPPy6wBBYnJycnJydnnKnbZJPkSs8vvyywBBYnJycnJydnnMmssUYSWO+/L7AEFicnJycnJ2eEaZg/P7nS80or1cryFFg2aE5OTk5Ozo7uXDh2bPIx7uuvL7AEFicnJycnJ2ecmffOO8mnjG65pcASWJycnJycnJxxZs7zzydvIdx9d4ElsDg5OTk5OTnjzMyHHw6BVf+lLwksgcXJycnJyckZZ6bfeWcIrHHf/KbAElicnJycnJyccWbKL38ZAmvCd78rsAQWJycnJycnZ5yZ9MMfhsCafNllAktgcXJycnJycsaZCWeeGQJr6o03CiyBxcnJycnJyRlnxh5zTAisGX/4g8ASWJycnJycnJyReAceGAJr1t/+JrAEFicnJycnJ2ecKXzhCyGw5v797wJLYHFycnJycnLGmdymm4bAmp9KCSyBxcnJycnJyRlnMn36hMBaNHmywBJYnJycnJycnDFm4cJU9+6pHj0WNzQILIHFycnJycnJGaOvJk5MdeuWWXfdGlqeAssGzcnJycnJ2aGd8//1rxBYuc99TmAJLE5OTk5OTs44M+fFF0NgFXbZRWAJLE5OTk5OTs44M+vRR0Ng1R98sMASWJycnJycnJxxZvqwYSGwxh53nMASWJycnJycnJxxZur114fAmvCd7wgsgcXJycnJyckZZyZdckkIrEk/+pHAElicnJycnJyccWbCWWeFwJp6/fUCS2BxcnJycnJyxpmxxx8fAmv6sGECS2BxcnJycnJyRrIdckgIrFmPPiqwBBYnJycnJydnnCnuumsIrDkvviiwBBYnJycnJydnnMltvnkIrPnvvy+wBBYnJycnJydnnMmut14IrIUTJggsgcXJycnJyckZYxoaUj16pLp3X7xwocASWJycnJycnJwRZtGUKalu3TJrr11by1Ng2aA5OTk5OTk7rnN+Oh0CK/fZzwosgcXJycnJyckZxzn3lVdCYBX69xdYAouTk5OTk5MzjnPW44+HwCodcIDAElicnJycnJyccZwz7r03BNbYIUMElsDi5OTk5OTkjOOc+utfh8Aaf8YZAktgcXJycnJycsZxTr7sshBYk37wA4ElsDg5OTk5OTnjOCd897shsKb84hcCS2BxcnJycnJyxnGO++Y3Q2BNv+MOgSWwODk5OTk5OeM467/0pRBYM//yF4ElsDg5OTk5OTnjOIt77BECa85zzwksgcXJycnJyckZx5nbaqsQWPPeeaezBVa3paY1XxdYnJycnJycnNVO9pOfDIG1cOzYThVYy8fT8r9v6u8ILE5OTk5OTs5WTrpXrxBYDfPmdYnAqvbrAouTk5OTk5Oz2lk0fXqoq8waa9Tc8uwQgfWIMcYYY8xy8/jtt4fAenf99WvI3KrXYDmCxcnJycnJydnWzrmjR4fAKuy4oyNYAouTk5OTk5MzjnP2E0+EwCrtu6/AElicnJycnJyccZwz7rsvBNbYr361qwTWYu8i5OTk5OTk5Gxj57Sbbw6BNf7UUztbYC32OVh2PE5OTk5OzhXknHzllSGwJl50UScMrPb4fgKLk5OTk5OTc7mZeP75IbCm/OxnAktgcXJycnJycsZxjjv55BBY0267TWAJLE5OTk5OTs44zjFHHhkCa+af/yywBBYnJycnJydnHGfxi18MgTX7mWcElsDi5OTk5OTkjOPMb7NNCKx5b74psAQWJycnJycnZxxndoMNQmAtKBYFlsDi5OTk5OTkjONMr7JKCKyG2bMFlsDi5OTk5OTkjOBsmDUr1FW6d+9aXJ4CywbNycnJycnZEZ0LCoUQWHUbbSSwBBYnJycnJydnHOe8N94IgZXfbjuBJbA4OTk5OTk54zhnP/10CKzSoEECS2BxcnJycnJyxnHOfOCBEFhjBg8WWAKLk5OTk5OTM45z2q23hsAaf8opAktgcXJycnJycsZxTrn66hBYE7/3PYElsDg5OTk5OTnjOCdeeGEIrClXXSWwBBYnJycnJydnHOf4//mfEFjTbrlFYAksTk5OTk5OzjjOMV/5SgisGcOHCyyBxcnJycnJyRnHWdpnnxBYs598UmAJLE5OTk5OTs44zvwOO4TAmvvaawJLYHFycnJycnLGcdZ9+tMhsBbkcgJLYHFycnJycnLGcWZWXz0E1qIZMwSWwOLk5OTk5OSM4GyYOzfUVXrllWt0eQosGzQnJycnJ2eHcy6srw+Ble3bV2AJLE5OTk5OTs44znn//GcIrPzWWwssgcXJycnJyckZxznn2WdDYBX33FNgCSxOTk5OTk7OOM6ZDz0UAmvM4YcLLIHFycnJycnJGcc5/fbbQ2CNO/FEgSWwODk5OTk5OeM4p1xzTQisieeeK7AEFicnJycnJ2cc56Tvfz8E1uQrrhBYAouTk5OTk5MzjnP86aeHwJr2m98ILIHFycnJycnJGcc59uijQ2DN+OMfBZbA4uTk5OTk5IzjLO2/fwis2SNHCiyBxcnJycnJyRnHWdh55xBYc199VWAJLE5OTk5OTs44zrp+/UJgzc9kBJbA4uTk5OTk5IzjzKy1VgisRVOnCiyBxcnJycnJyRnB2bBgQairVM+eixsaBJbA4uTk5OTk5IzgXDh+fAis7Cc+UbvLU2DZoDk5OTk5OTuWc/5774XAym2xhcASWJycnJycnJxxnHNGjQqBVdxtN4ElsDg5OTk5OTnjOGeNGBECq/7QQwWWwOLk5OTk5OSM45x+110hsMZ9/esCS2BxcnJycnJyxnFOvfbaEFgTzj5bYAksTk5OTk5OzjjOSRdfHAJr8o9/LLAEFicnJycnJ2cc54RvfzsE1tQbbhBYAouTk5OTk5MzjnPssceGwJpxzz0CS2BxcnJycnJyxnHWH3RQCKxZjz0msAQWJycnJycnZxxnYcCAEFhzX35ZYAksTk5OTk5OzjjO3GabhcCa/8EHAktgcXJycnJycsZxZtZZJwTWokmTBJbA4uTk5OTk5IzhXLQo1b17+BV+I7AEFicnJycnJ2cE56JJk1LdumXWWaeml6fAskFzcnJycnJ2IOf8Dz4IgZXbbDOBJbA4OTk5OTk54zjnvvxyCKzCgAECS2BxcnJycnJyxnHOeuyxEFj1Bx0ksAQWJycnJycnZxznjHvuCYE19thjO39gdfvPNPrFCr8usDg5OTk5OTmbnam/+lUIrAnf/nYnD6yl66fR3y8fWNVmk8Di5OTk5OTkXDKTL700BNakiy/uzIHVVPpUGFUVlpPA4uTk5OTk5FwyE84+OwTW1Guv7fyBtfwpv7iB9YgxxhhjzL9n9D77hMB67txza9RfaWAtHU/VnhZ0BIuTk5OTk5OzOsmhh4bAmjViRBc6RSiwODk5OTk5OdvUWdxttxBYc154QWAJLE5OTk5OTs44ztwWW4TAmv/uu505sJaJJ+8i5OTk5OTk5GxTZ/YTnwiBtXD8+M4fWD4Hy47HycnJycnZHs6GhlTPniGwGhYs6OSB1R7fT2BxcnJycnJyLl68aOrUUFeZtdaq9eUpsGzQnJycnJycHcU5P5MJgVXXr5/AElicnJycnJyccZxzX301BFZh550FlsDi5OTk5OTkjOOcPXJkCKzS/vsLLIHFycnJycnJGcc5449/DIE19uijBZbA4uTk5OTk5IzjnPab34TAGn/66QJLYHFycnJycnLGcU6+4ooQWJO+/32BJbA4OTk5OTk54zgnnntuCKwp11wjsAQWJycnJycnZxznuBNPDIE1/fbbBZbA4uTk5OTk5IzjHHPEESGwZj70kMASWJycnJycnJxxnMWBA0NgzXn2WYElsDg5OTk5OTnjOPNbbx0Ca94//ymwBBYnJycnJydnHGe2b98QWAubvq3AElicnJycnJyc1U165ZVDYDXMnSuwBBYnJycnJydnBOeiGTNCXaVXW60TLE+BZYPm5OTk5OTsEM4FuVwIrLqNNxZYAouTk5OTk5MzjnPua6+FwMrvsIPAElicnJycnJyccZyzn3wyBFZpn30ElsDi5OTk5OTkjOOcMXx4CKwxX/mKwBJYnJycnJycnHGc0265JQTW+P/5H4ElsDg5OTk5OTnjOKdcdVUIrIkXXiiwBBYnJycnJydnHOfE730vBNaUq68WWAKLk5OTk5OTM45z/CmnhMCaduutAktgcXJycnJycsZxjhk8OATWzAceEFgCi5OTk5OTkzOOszRoUAis2U8/LbAEFicnJycnJ2ccZ3677UJgzXvjDYElsDg5OTk5OTnjOOs22igE1oJCQWAJLE5OTk5OTs44zvSqq4bAapg1S2AJLE5OTk5OTs4IzoY5c0JdpVdZpXMsT4Flx+Pk5OTk5FzxzgXFYgis7AYbCCyBxcnJycnJyRnHOe/NN0Ng5bfZRmAJLE5OTk5OTs44ztnPPBMCq/jFLwosgcXJycnJyckZxznzz38OgTXmy18WWAKLk5OTk5OTM45z2m23hcAad9JJAktgcXJycnJycsZxTvnZz0JgTTz/fIElsDg5OTk5OTnjOCdedFEIrMlXXimwBBYnJycnJydnHOf4U08NgTXt5psFlsDi5OTk5OTkjOMc+9WvhsCacd99AktgcXJycnJycsZxlvbdNwTW7CeeEFgCi5OTk5OTkzOOs7DjjiGw5o4eLbAEFicnJycnJ2ccZ91nPhMCa0FdncASWJycnJycnJxxnJk11giBtWj6dIElsDg5OTk5OTkjOBvmzQt1le7Vq9MsT4Flx+Pk5OTk5FzBzoVjx4bAyn7ykwJLYHFycnJycnLGcc57550QWLmtthJYAouTk5OTk5MzjnPO88+HwCrusYfAElicnJycnJyccZwzH344BFb9l74ksAQWJycnJycnZxzn9DvuCIE17pvfFFgCi5OTk5OTkzOOc8ovfhECa8J3vyuwBBYnJycnJydnHOekH/wgBNbkyy4TWAKLk5OTk5OTM45z/BlnhMCaeuONAktgcXJycnJycsZxjh0yJATWjD/8QWAJLE5OTk5OTs44ztIBB4TAmvX44wJLYHFycnJycnLGcRb69w+BNfeVVwSWwOLk5OTk5OSM48x99rMhsOan010usLr9e5b/SuVfF1icnJycnJycjU5m7bVDYC2aMkVg/beKKvy6wOLk5OTk5ORsZBYuTHXvnurRY3FDQ9cKrCUBtHQGVRtbAouTk5OTk5Oz8b6aMCHVrVt2vfU60/JsPrAajae4gfWIMcYYY7rqjLzllhBY72y4Yef4cTpQYDmCxcnJycnJ2WWdc158MQRWcdddu9ARrKaiSmBxcnJycnJyRnHOevTREFj1hxzStQJrmRFYnJycnJycnBGd04cNC4E19vjju9ZrsFp81Mq7CDk5OTk5OTmbnUlDhwqsxY0e3Krk6wKLk5OTk5OTc/kpDBgQAiv8t4sGVht+P4HFycnJycnZJZ2Lpk9Pr7pqCKxpd94psAQWJycnJycnZwTn1BtvDHVV2nvvTrY8BZYdj5OTk5OTc4U581tvHQJrxvDhAktgcXJycnJyckZwzn7qqVBXdRtt1LBggcASWJycnJycnJwRnGO+8pUQWJMvvbTzLU+BZcfj5OTk5ORcAc4FxWJ6pZXSvXotHDNGYAksTk5OTk5OzgjOSRdfnHz81ZAhnXJ5Ciw7HicnJycnZ3s7G+bPz37qUyGw5jz7rMASWHY8Tk5OTk7OCM4Z994b6iq//faddXkKLDseJycnJydnezuLAwcmHy56880CS2DZ8Tg5OTk5OSM4573xRqirzNprL5o5U2Ct+MCa9/bb4884Y94779igOTk5OTk5a9c5/tRTQ2BNOPvsTrw8aymwQl0l6+PMM23QnJycnJycNepcNHVqZvXVU927z3/vPYHVUY5gJUcU11hj0bRpNmhOTk5OTs5adE697rrk4oP779+5l2ctBVaY0r77hrUS1o0NmpOTk5OTs/acDQ25LbYIT+UzH3xQYHWgwArrI6yV3OabhzVkg+bk5OTk5Kwt5+yRI5OLD37mM4sXLhRYHSiwwvqo22STsG5mPfaYDZqTk5OTk7O2nGO+/OXk4oM/+UmnX561FliLF0/56U/Duqk/7DAbNCcnJycnZw05F+RyqZ490yuvvHDcOIHV4QJr4cSJ6d69k3cfpFI2aE5OTk5OzlpxTho6NLn44PHHd4XlWXuBFWbcySeHNTTxnHNs0JycnJycnDXhbJg7N7v++snFB0eNElgdNLDmjh6dfF5Dnz5lPgHWBs3JycnJydlxnNOHDQvP3YWdduoiy7MmAytMcc89y1/DyAbNycnJycnZcZzF3XZLnrhvu01gdejA+vAq3Ntua4Pm5OTk5OTs4M65//hHcuppnXUaZs8WWB06sBrmz89usEFYW7OfftoGzcnJycnJ2ZGdH754+txzu87yrNXACjP50kvD2hpz1FE2aE5OTk5Ozg7rXDR5cnrVVZO3/3/wgcCqgcBaOGZMulevVM+eC/J5GzQnJycnJ2fHdE655prkAywPPrhLLc8aDqwwY487LqyzSUOH2qA5OTk5OTk7orOhIbfZZsklWEaMEFg1E1hzRo0K6yz7iU80zJ1rg+bk5OTk5Oxozll//Wty8cF+/RYvWiSwaiawwhT69w9rbvqdd9qgOTk5OTk5O5qz/rDDwtP0lKuv7mrLs+YDK6RV8sFl/fvboDk5OTk5OTuUc34mk+rRI92798KJEwVWjQVW8tH7n/hE8tH7L75og+bk5OTk5Ow4zonf+154gh53wgldcHnWfGAt/ujikccdZ4Pm5OTk5OTsKM5sNrveeuEJeu7f/y6wajKwFuTzqZ490yuvvHDMGBs0JycnJydnR3Dmr702eQ3PgAFdc3l2hsAKM+aoo8JanHzppTZoTk5OTk7OjuDM7LBDo+9CE1i1FFizn346+byGDTZomD/fjsfJycnJyblincVHH02el9dbr2HOHIFVw4EVJr/ttmFdzvjjH+14nJycnJycK9ZZ97WvJRcfvOCCLrs8O09gTbv55rAui3vuacfj5OTk5ORcgc7SP/+ZWnnlVI8e8zMZgVXzgbVo5sxMnz7JuxVGj7bjcXJycnJyrihn/gc/SM4PHnBAV16enSewwkw855zk8zZOPtmOx8nJycnJuWKcxWL6059O3j94zz0Cq5ME1vxUKtW9+5JPjLXjcXJycnJytr+zcNddoa7S/frVl0oCq5MEVrLcDz10yTWP7HicnJycnJzt78zuvXd4Is5dckkXX56dLbBmPfZYctXuTTapLxTseJycnJycnO3pLI0alerePdW7d/277wqsThVYixsacptvnpz6vf12Ox4nJycnJ2d7OnOnnpoc5jj2WMuz0wXW4sVTr7surN3MwIF2PE5OTk5OzvZzptOptddOPjJp5EjLsxMG1qKpUzNrrJGs4GeeseNxcnJycnK2jzN/zTXJAY7+/S3PzhlYYcafcUbyCrsTT7TjcXJycnJyto8zs802yUt0brzR8uy0gTXv7beT94iuvnrp/ffteJycnJycnG3tLD78cPLM+4lP1OdylmenDaww2YEDw5rOX3aZHY+Tk5OTk7OtndnBg5NzR2efbXl28sAq3H57ktKf/Wx9qWTH4+Tk5OTkbDtn6c03U716pXr2LL3yiuXZyQOrvlBIb7zxko/qt+NxcnJycnK2nTN34YXJxQcPPtjy7AKB9dHFJvff347HycnJycnZVs5CIb3hhsmb9//0J8uzSwRW6e23U6uskurevThqlB2Pk5OTk5OzLZyF3/0ueU3OZpst/5ocgdU5AytM9phjktfcnXqqHY+Tk5OTk7MtnJkl7yq7/HLLswsFVnHkyLDWU2utVUql7HicnJycnJxxnaXnnksOX622Wum99yzPLhRYSVkPGJCU9dVX2/E4OTk5OTnjOutOOSW5+OA3vmF5Vh1Y3Zaa1nx9RQVW4aabkk/u32orOx4nJycnJ2dEZymVSq+5ZniSLT35pOVZXWAtnT7LNNNHv18+sKrNpjYNrFIul+7bN/m8hvvvt+NxcnJycnLGcuavvjo5hLHrrpZna08RVhtVFZZTmwZWmNz55yef13DooXY8Tk5OTk7OWM7M1lsnxy9uvtny7KCB9Ugbz9+GDUuttNIHPXo8fuedjxhjjDGm1fPUvw9fvbfOOo889JClsfRUHViNnh+siSNY9R9dI+mss/zLhpOTk5OTs/XO7BFHJE+s555rebbqCFb5cur4gVUcMSJ5H+m669bX1dnxODk5OTk5W+MsvfZaulev9EorlUaPtjxbHljLB1DNBVZyqnj77ZPPa7juOjseJycnJydna5wfvrj5sMMsz5YHVlP1UyvvIvxoQlolb3bYfns7HicnJycnZ4udpXz+w7fnDx9uebYwsLotN43+0TK11KE+B+u/U1eXXnfdZIMYMcKOx8nJycnJ2TJn/re/TQ5YbLGF5dnaU4Rt/v3aJ7Dq63NnnZUc0hw82I7HycnJycnZMmd2jz2Sl7f/5CeWp8D6z1HNV19N9eyZ6tWr9PrrdjxOTk5OTs5qnYXhw5M3ja2+eulf/7I8BdZS3X3ooUl3n3++HY+Tk5OTk7MKZ6mUv/rqdK9eyfnBTTe1PAXWx9P7/vuT9O7bt5TL2fE4OTk5OTkrcZaefz67227hCTSpq898pvDAA5anwFp2MlttVf6j/W0onJycnJycH6ZVPp8bOjS1yirJ4YlPfjL/299angKr8fnw4pQDBtjxODk5OTk5yziLjz2W/vznlxy4yh5zTP2771qeAqvp45ypVGqttcK2Uhw50obCycnJycnZiDOdzp1+evLOsG7dMv36Fe67z/IUWM2vgNypp34Y4zYUTk5OTk7OjzuL992X2WST5MBVz565M86oz2QsT4FV0QoojhqV6t49tcoqpbfftqFwcnJycnJ+eNfvvpsdMuTDF7Nvs03xb3+zPAVWdSsgu99+yaUJf/hDGwonJycnJ2e42/wtt6TXXz+pq1VWyQ0dWsrnLU+BVfUKKNxzT/KGiI03ri8UbCicnJycnF3ZuaBYzB500IcvZt9999Lzz1ueAqulK6BUSn/2s8nnNdx+uw2Fk5OTk7OLOhsapt18c+bf7/1Kr7VW/mc/C8+PlqfAatUKyF92WXKOeeBAGwonJycnZxd0zn///dJee3144Orgg0uvvWZ5CqwIK6D03nvp1VZLDmI9+KANhZOTk5Oz6zgbFiyYfOWV6d69k7T61KdmDB9ueQqsmCsg3a9fclB0tdWKI0bYUDg5OTk5u4Jz7iuv5HfYYcmBq3Enn7xo8mTLU2BFXgGFBx/M9O2bbGS9euWuvNKGwsnJycnZiZ0Ns2ZNPO+8JR8fmttss9lPPml5Cqy2WgHJVZb+/bmj4Vfd0UeX+Tg1DxCcnJycnLXrnP3EE7lNN13y8aETzz+/YfZsy1NgtfkKKNx005LXY2W23bb40ks2FE5OTk7OTuNcNHnyuJNOWnIoobDjjnNffdXyFFjttwKKTz215IMbUn36FO65x4bCycnJydkJnDPuuy/77xfDpHv3nnzllQ0LFlieAqu9V0DpvfeyBx6YNFaPHrkLLljms0A8QHBycnJydlznokULJ06c/69/zXnppVmPPjp92LDJl12W23LLJQeuSoMGzX//fctTYK24FVAqhbQKgZW8c/XAA0Ny2VA4OTk5OVeYs1gsvf126YUXCo88Uhg2LP+rX+Uvv3zSJZdM+M53xh53XP3BBxcGDMhttllmnXWSa+z+u6WW+ZVeZZVpt9yyuKHB8hRYK34FFP7wh1SfPsl2+dnPFp96yobCycnJydl2ztLrr+cuuiizyy51hx2WHTw4u88+mR13zPTrl1p77aayqZFfPXqEzMp97nOFXXYJ4TX2+OPHnXxyfrvtZtx/v/UusDrQCii+9FJm222XfEpW4aabPEBwcnJyckZzptPFhx7K/ehHdYcfnt5oo/LZFDIr3a9fZqedQnhljzqq7uSTJ11yydTrr59x992z/vrXOS+9NP+DDxZNmrR40SLrXWDVQGAlk8nUHX30kk08d+qpTb0w0AbNycnJydmMs1gsPvNM4dpr677xjcw226RXWuljZ/HWXDO93XaZXXcNzzWFG28s3H134ZFHSqNG1b/zTrih5SmwOl1g/XtyV16Z6tUreYXgXnstHDvWBs3JycnJWcksHDNm5kMP5c46KzNwYEiojxXVSitltt227pvfzF97bQivaq+vbL0LrM4QWMk/PEaMSP/7Pa51G244Z9QoGzQnJydnXOfC8ePDo+vEoUOLe+014bTTpl5//bRbb51x990zH3hg1l//Ovvpp+e89NK8N96Y/8EHC4rFRZMmNcyeXW2UtMPybJg1a85zz0255pqxX/ta3Wc+s+yLzTfeuO7ww3M/+lHxoYfKfKi17VNgdaHAClN6440llxxPr7zy1F//2gbNyVlbztLrr+eHDs0MGJD77nfDP5lKb71lea4o55KWmn7XXZMuvnjsMccU+vfPrL12pa/jXubXKqskr0/61KeSlyhtvXXyKqXdd09eqHTIIclrlY47ru7kk7Nf/nJm993rvv71/OWX56+5JjkBd9ttyTm4++9PTsM9+WRp1KjS6NHJybhMptm32i07ixbNe/vt6bffPv600wo77rjMib/MWmuV9tsvd/bZhTvvDE8i9neBJbAan4YFCyaec86HV8c84YRlLjJgg+bk7FjO5l5EnF5rrcwOO4Rn39w55+Svv36Z6rI84/zT9K23woINi7fZlsr06VP4whdCjpQGDRp73HETzjpr/Le+Nfb448ccdVT9IYeU9t67sMsu+e22y33uc3UbbZRZd930qqtW8fa6an6le/fOrLNO+C7he4XvGL5vINUffPCYwYODJ6iCLfymOHBgYeedQ0Itc+KvsNNO408/ffodd4TwWpJr9neBJbAqWgEz7r03s/rqydUGdtppfvjnjg2ak7ODOJt7EXFm++0zu+yS3Wuv0FXpjz8vLl9dIQim33XXnFGjFo4fb71X1VIhWJODRttv39RCXtJSY489NlnIv/99spAnTGiJs1RKTrS9805p9OjSqFHFJ58sPvpo4YEHkqNTt91WuPHG/DXX5K+4ImwP2T32yB55ZN3JJ9cdd1z2qKOyhx6a3Xff8MXMTjtltt463a9f+lOfSj6ap3fvFkRb3SabjP3a16Zcc82c555r9B/e9neBJbAqXQHz3nort/nmycPEuuvOeuwxGzQn54pytuZFxKV//jMJghtuSILgyCPLVFdm7bWTIDjmmFZW1zJBUHryyeSjI++//2NBcPnldV//emb33bNHH50777xmf0265JJKfo074YTioEHjTjyxkr9cyfcNv+qGDMnstltY8mVaKrUkWI88spUt1X7bZ0NDiKRFkyYtKBbnf/DBvDffnPvyy7OfeWbWX/8684EHZtx997Rbb516ww0Tzjyz9MUvTv7JTyp555P9XWAJrCpWwKKpU8ccccSSTyiZfPnlVZ+2t0Fztq8zPKvNe/31WY8+OuG888IT7YSzz54+bFj43+QTdP71r4UTJzb6CTodcHm29YuIP6qu5JTWsceGrmrylNa/q6u0777Fvfb62CmtwYPrDz64NGjQx05prbNOunfvtjif1YF+/aelklOuN9yQnHL95z/t75wCS2BVvwIaGkJaLbmoToitkFw2aM4V6GxYsGBBPj/nxRdnDB8+9brrJn7ve6EPSnvtldt004qe2rt3Tz4DerPNCgMGJJ8BHYrhO9/JnXde8rrgX/2qMGxY8nLgF14ovf12o5/K04bLswO8iDjkafKi7N//vtnqanYhJyeh+vT52Iuy99gjOV116KH/fVH2kUeGL9YNGVLJYaTJP/5xJb/GnXhiae+9w38r+ctVHcGqO/vsZVrK/s7JKbAirIBZf/tbZt11k08i3XzzeW+9ZYPmbFNnKZUqPf98Yfjw/A035L///dxJJ2UPPjgTsqNv3yWt39SvEE/5bbetP+ig+sMOKw4aNOaoo8Yef3xyFbNddsl97nPJVczK3nzZSlh77Uzogx13TN6uNXhw9pBD4p/SOvnkDv4i4iXVNfH73y8NGjTh9NOn3nDDxz5W4Jln5r788rw33+zgHytgf+fkFFgddwXMz2TCI37yHLb66jPuvdcG3QWdi2bMmHL11cU99xx3yikRX+OSHTIkhEtm332ze++d2XLLVFMvc/nP9TTqNtywMGDAmMGDJ3znO1Ouumr6sGGzn3pq/r/+1TBrViUHikIEhBqY89JLoQ9CKEy9/vrkKMXJJycvCt5nn8xOO6WXXBmt8hSL9MuLiDk5OQVWVwys5Gzh7NnjTjhhyZPBxHPOqfyiOjbo2nWGqJr12GMTL7ywuOuuy5y3asNfq6yS6dcvu9tu2cGDc2eemb/88sKttxZGjCj94x/tdymnYjF5mfaoUckLtO++u3DjjXWnnBL9lNb4U07xImJOTk6B1dUDa8lM/fWv0yuvnPyDe+ONZ40YUckr323QzZyFGTNmylVXFffYY/Lll89/993FCxeuWGdTURV+n//854sDB47/1rcivsZlyRGsutNPLwwblnwc4ttveyDj5OTkFFhdLrDCzBk1KrPGGkuedLMbbDD+jDNmP/FEmUMLNuhljwWWf49Y796FnXced+KJU375y9n/938Lx41rB2eZqCruttvEiy6a9be/hb/jgYyTk5OTU2C14QqYPXJkfsstc0vFQWbddUMTzHz44Ya5c23Qyzqbe49YoX//4p57lr74xbp+/Zb/DMBs376l/fefeO650++8c+7o0fXZbBRb6YMPCvfcU/ftb2d33jlWVFnvnJycnAJLYEVYAeH5ftIPf5j//Of/mwtrrjl2yJAZf/rTR8/NXXODLr3+euGOOyYNHVrab79K3iP23zN006bNeeGFaTfdNP6MM4oDBzbyVvmePTObb5494ojchRcW7rqr9Pe/d5yo8kDGycnJKbAEVswVMP/ddyf/5CeF/v2XPtU15ogjpt95Z/2773aJDbrsVeGafY9YmVlQVzdrxIiweEO55rfeOgTWsmcV11wzM2BA3Qkn5H/60+Jf/lJ6//0Koyrbv3/dd75T+MMfYkWVBzJOTk5OgSWw2mQFhBqY8stfFgcO/OiN7snVPPbaKzz3l15/vd2cSy5lP3Ho0OJee0047bSp11//sc/vefrpOS+9NO+NN1r1+T3NXhVu4MBJ3//+zL/8pZL3iFWx3uvqiiNH5q+7Lnf66WHBptdfv5GLzX3605ldd8184QuZLbZoKqpCeHmA4OTk5OQUWDW2AhaOGTPtpptKBxzw3yf4Hj0yu+yS+/GPqzqr1axzSUtNv+uuZi9lX8kHBKTWXvtjn0C9++7J50wecsh/P4H6qKOyoV22266Sq8K1z45XevPN4n33hQWbfOr09tsnP8XHYY1GlQcITk5OTk6BVcsbyrvv5q+7LnvggUs/8YdAyV10UenZZ6t7YdN/LmXfbEstuZR9ab/9SoMGfewaakcdVX/IIaW99/7YNdTWXTe96qotuMJ8s1eFWzE7XqEQFmzdhRdmBgzIh5xtIqo8QHBycnJyCqzOsKGEZ/r8Lbdkjzgi/Z9PeUhKaPPNc9/9bnHkyKZaKnfOOdkvf7nMpeyXtNTYY49t5aXsk2NOIZLeeac0enRp1Kjik08WH3208MADyedM3nZb4cYb89dck7/iityJJ2Z33TWpwwquCucBgpOTk5NTYAms9tpQ6uoKd91VN2RIqk+f/3ZS376ZnXfODhpUpqU+upR9K1vKjsfJycnJySmwOu2GUsrnkxcPnXhich3fJloqd845+RtuWOZS9nY8Tk5OTk5OgSWwmn11VSl/1VWZ/v1zF1ywTEvZoDk5OTk5OQWWwOLk5OTk5OQUWALLhsLJycnJyckpsGwonJycnJycnAJLYHFycnJycnIKLIHFycnJycnJySmwbCicnJycnJycAsuGwsnJycnJySmwBBYnJycnJycnZ4WB1W2pEVicnJycnJycnHECq+0ySGBxcnJycnJydrnAWiZ92qixBBYnJycnJyenwIo8jxhjjDHGdIrpQIFljDHGGNPpR2AZY4wxxggsY4wxxphaCazF7fIuQmOMMcaYLhdYbf05WMYYY4wxXSuwVoyg4qqrsPy6fXxa/31j/YAtcJb507bwN3qfrVyeXdnZ6HZbobOpbT66sylPVdtnuy3PFq/3pvamtl6eS58WqHZ5NvVj2t9XoLPax+Q2epxfIUdD2sLZ4ue4mjgS1CECa5nftD6wqnrOa5+V1Ghgtea20f3LPyhUtTybum2bOhdXeV67zG3bbntY/gG3lXHWpsuz2v2oPfevRhdjhfff1G3b+nGgNfdvPypzn615nG+9s6mn/JY5W3CfK/D1POWfy5p6uGv2Hz+V36fAau1O3tTfjBhYLWudjhNYbe2P9cTQxZ3Lb7fVrvcyt43ibKPA6rLOZquu9bdti+UZK7C6iLPyx+S2eJxfse9Iq+RQSMue36tdlQIrTuhUu1NVcliyIwRW5ac2VmxgVXs4ekUFVkdzlvnXZyWnNtrtiTb6KcK2e6JtsbOp27ZnYFW1fa7AwGrx42fXcVYVQ9Ef57t4YNXQu/E6YWAt/wRQ/uvtc6SxkleHVBtnbeev5NRP5U8qbeGs5Im/8tu2kbPZ7baS54b2WZ6V7y+V3LYtnJXcZ7X7e5suz2a3wKoeGNto+2zxflQmyrvCem/ZP3pb8DhfJtra8/mrqueyFvzDoNrdQWDF+dfJ4tYdZm/qPst8i45Q/ZW8aqft/BVu6029pLHdnJVHeZnH37ZzVrjdVrvNW54tcJa5bZfdj2poeVZyn9U+zrfS2eKzClU9zq+Q7baV/3Ko9vm9NfcpsCLs5GXeWROlbDpaYMW9bWd1Vv5A1ka3rerwQOVnMVp/2068PFv8vVpz2866H9XW8uxo22frA6t97rM9n8ta81KWqu6zNT3QtQJrcetetFjJkYNK/qm9QjbKSpwV3rZN95wKne22nCs5XFzJel/c6nf9tP5oVgtOubbp8qzkXVctuG1bPFZU5azwtl1qf6+V/aiS7b/ax/nWO1v2LsJq13uF97liD4tUWEjVvv5sRf2LvRMGVste+NnK+2y3/m3NZwVVcts2clb1GTyV3LYdtpkon4vTDg9Jrdnmu/LyrCFnax6X2u3xqubWe8TH+RY7W/B43hafJ7dCjt9U+IaY1jx3VHWkSmAZY4wxxnS5EVjGGGOMMQLLGGOMMUZgGWOMMcYILGOMMcYYI7CMMcYYYwSWMcYYY4zAMsYYY4wxAssYY4wxRmAZY4wxxggsY4zpXI+J1VyPq6qbNHpbY4zAMsbUajHUxJXno3RP6++58sBqjU1gGSOwjDG1XVed43ldYBljBJYxpga6pKkjW41exL5MhTR6P0t+X/7+K8GU/0Fa/K0/+qOmftKqMI0usTJf11jGCCxjTOcMrGWSopLfN3q3ldy2zN9v9oZlfpBWfusyP1qzR6fK3KRClcAyRmAZY2q+sZo6zNNohbTn18v/5WYDq02pLQa35p6NMQLLGFOTsbV8dVV4pKot7qf8nTQbWLF+BIFljBFYxpg4gVX+L7SsTqq9n8pTo/LXMAksY4zAMsa0U1Et/9zf4hcqVfiCp2a/b7N30mxgteZbtzKDKlkglSwoY4zAMsbUamNV9ca9Zt8Tt7jidxGWyZEWvIuw0bOBLfvWjd5JKwOrqncRCixjBJYxpkvHmR+tTPC17Fv4JHdjBJYxRmB1wh+nfRJHRRkjsIwxpkskQnteNUhgGSOwjDHGGGOMwDLGGGOM6ajz/wHQOQnIVIzD+wAAAABJRU5ErkJg" alt="Sequence length distribution" width="800" height="600"/></p></div><div class="module"><h2 id="M8"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAFlUlEQVR42s2XCUzTVxzHybIs0IgCLYqyQ9RtmhjCNKKbikajYVc22NThNjYjeC0yWBESxAV1Ckw8QEUF5ChnS4FyFETucwWU+7ClHKKiImLI4nCz9bv3/pS7ra1HtM1Lm/b/fp/ve+93PQMABq9y6D/Bz+ANNvethWxPw3Xs3wx/YAb9Tn6j/700AeZc1qccrhGPw2UNkk8Fx9voIceX9Tcz6Hf62/B/PPrsCxNgzjW043iyGjheRkOWQRzFt2IH/Nl4DDFyHjJ6siDoSoZ/YwB2VuyEffpGzA5iK+izdA6d+8wCyHa+SYyEsj2N/jU/aaL0vbIf0sF2tA92oOVBG+ruN6CqrwZldypR0FuMnBuXkX49C5GyaGwq3ASLU2ZKOpfaoLb0EmDibmLC8TQq5/iw/vlIaA1xjxiyQTmaH7Sitr8ekr5qlN6pQP6tImTfyIXoeiYEnSmIlSfiooyHc20R8G84htUZq0FtUFvUpk4ChldO4H6sRzvKXdEw0ISmgRZc7a/DXwRccrscebcKIb5xCWndGeB3CsGTJyBCGoPQtnCcajlLjugk/qgPxO+1h7Eqyw7UFrWpbiemCKBbRlW7lrmgcaAZV/prUXm3CsW3y3D5VgGyenKQ2p2OpM5k8NoTEC6Nxtm2MJxsPoPAxhM4XB+AA1cPwbvmADyqvPFLpQdsM1aodoIVqlUAdRp6bgv5HzBbXHFXgqLbpci9mY/MnmykdIuQ2CFATHs8wqRRONN6ASeaTyOg8TgO1fnDl4C9anzhLvHCnkp3uJTvgXOJC7YUOWN+0nww/jTJMSevvsHs+DRlSOsZFPaW4NLNPOLpYgi70pBAwFHtcbhwLRKnW8/jeHMIOecgHKw7iv1XD2Jf9X78KtmHyNZoiOQi/FiyHZsJ+Ov87/DZZUesEq8H+4SxkjLUCmDinISPY74jcm4Oe3RyVyriO/iIksUS8EWEtJ5DUFMwjhIH86s7Ap8rfvCs9oGbxBO7KtwQ3hKBrgdd6H94D3ypgIAdsD7nc6wWb8DyzDWYy58HyhifJ8ZWT5NMoLGCJ48jsZ2COHkSCSkezl+LQHBLKI40BGJLsRPW5qzDskxbLE5bDBuRDWwzV5DV2SGwNhCdAx0Yed172AdeWyyWpa/ColQbzE1+H7MTLcEOmKagrAkCaAqlWWwZf6kqlMY8+gDZ3jXZazEz0Rym8TPUDg+yetl9Kca/HikeIUUmgEXizAnPml2YDsoaSduMAJrHaSrdWvw9AYcR8LBHu0m4eJtvqRGsDS4k8DlJFlPnxM0AZVHmmABSTGg+31GxW+XRAfi51AWztKxaI/zxELNytXDVoCzKHBNAKhotKrsr9zIe7Vq+G5wEs9EJi1I+hFDKx7zkuTrAk7XCGQGERZlTBLiSuN1Ltn2BcMEEeGF3PoaI8dzObFgJ3nsuuHoBqiNwLNgMu+x1ow9SByrsyoNC+ZiBPFb8h5LrhWrhqTKhTnD1R6BywuWZn0zYejq2FTuj/k7tKEz5RPlccLVOOBKG7DATtZO+yXNATW81npD3ZHhaux5wTWE4kohoktA0cWPOelT3SkZFDMNT9ICbwCJplvpEND4Vm8ZqNrJBJWJIT7h5Ioek5a+wRLRUcyoeX4y0GaMiaEjqCn9X8A62le0ADXGLYLbmYjS+HJtGTdf5TLUNa5E1Kc8+8K09iPkJVk8vx+MbEm1H8bTBTjDFF3lfMlmVNipLREt0a0gmt2TPIsKKZEv3Ki5TU2gZt8+1168lm9yU6noc1MO3FDkxYNojhpH+YW2Gnf5Nqbq2nHHMWPVbbZNuA6firQghpZt2TRHSSGwn/eScYPNnb8s1XUxoDFtGWpD6sAgrxSvhSi4juypJ31f6ExwLSNsl/BicAOMXczF5ba5mr83l9GWN/wE1f784zfWjGwAAAABJRU5ErkJg" alt="[OK]"/>Sequence Duplication Levels</h2><p><img class="indented" src="data:image/png;base64,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" alt="Duplication level graph" width="800" height="600"/></p></div><div class="module"><h2 id="M9"><img src="data:image/png;base64,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" alt="[FAIL]"/>Overrepresented sequences</h2><table><thead><tr><th>Sequence</th><th>Count</th><th>Percentage</th><th>Possible Source</th></tr></thead><tbody><tr><td>TTAGACGGATCCACTAGTTCTAGAGCGGCCGCCACCGCGGTGGAGCTCCA</td><td>146</td><td>3.3249829196082894</td><td>No Hit</td></tr><tr><td>TT</td><td>92</td><td>2.0951947164654974</td><td>No Hit</td></tr><tr><td>TTATACAGCAAGCGCGCACCGACTCTGACAATCGGCATATCCGGTTCGCC</td><td>86</td><td>1.958551582782965</td><td>No Hit</td></tr><tr><td>TTAAAACCTCTTCAAATTTGCCGTGCAAATTTGGTAGGCCTGAGTGGACT</td><td>83</td><td>1.890230015941699</td><td>No Hit</td></tr><tr><td>TTA</td><td>74</td><td>1.6852653154179003</td><td>No Hit</td></tr><tr><td>TTGGCGAAGTAATCGCAACATCCGCATTAAAATCTAGCGAGGGCTTTACT</td><td>50</td><td>1.1386927806877705</td><td>No Hit</td></tr><tr><td>TTTACCAGCATTAAGGAACAGCTGCTTACGGTCGGCGTGGGTTGCCAGCA</td><td>32</td><td>0.7287633796401731</td><td>No Hit</td></tr><tr><td>ATCACAGGCGTAAACGTCGCCGTTGTGCTCAACAATCACCGAGCGCCCAC</td><td>30</td><td>0.6832156684126622</td><td>No Hit</td></tr><tr><td>TTAT</td><td>26</td><td>0.5921202459576406</td><td>No Hit</td></tr><tr><td>AT</td><td>23</td><td>0.5237986791163743</td><td>No Hit</td></tr><tr><td>GTACGATGTCACTGTGCACGACGATGGTCACTTCCAAGGCGCGGAGTGCC</td><td>19</td><td>0.43270325666135273</td><td>No Hit</td></tr><tr><td>ATCATCGTACGCAAGTGACCAACGCTGTCGATGGTGTCTTTGATGCCAAC</td><td>17</td><td>0.38715554543384195</td><td>No Hit</td></tr><tr><td>TTATCCAGCGCGAGCACTCGCTCTATCACCATTTCACGAGTTTCAAGGTT</td><td>16</td><td>0.36438168982008656</td><td>No Hit</td></tr><tr><td>ATGAGGAGCGAAGGCATGAAACCATATCAGCGCCAGTTTATTGAATTTGC</td><td>16</td><td>0.36438168982008656</td><td>No Hit</td></tr><tr><td>ATATAGAGCATTTTTGCCTCCTTTCGCGCCACAAGAAATTAACTGTAGCG</td><td>15</td><td>0.3416078342063311</td><td>No Hit</td></tr><tr><td>TTAGGCGACAACGTGATGGTTGCGCCGGTGTTCACTGAAGCGGGCGATGT</td><td>14</td><td>0.31883397859257573</td><td>No Hit</td></tr><tr><td>TTG</td><td>14</td><td>0.31883397859257573</td><td>No Hit</td></tr><tr><td>TTATCAATACTGCCTTCAATCAGTACATTGGTGGCAGGAACATCATTGAG</td><td>14</td><td>0.31883397859257573</td><td>No Hit</td></tr><tr><td>TTATCCGAAGCGATGAGAGTTATCCCGTAACCGGGTCAGCCACTGCATAG</td><td>14</td><td>0.31883397859257573</td><td>No Hit</td></tr><tr><td>TTACGCATAGTCATTTCTCCTTCTAAGAAGCGAGTAAGTACCTGCAAATC</td><td>13</td><td>0.2960601229788203</td><td>No Hit</td></tr><tr><td>TTACGCATAATCAATAGCTCCTGAAATCAGCGAGAATGTAAGACCTTCCA</td><td>12</td><td>0.2732862673650649</td><td>No Hit</td></tr><tr><td>TTAG</td><td>12</td><td>0.2732862673650649</td><td>No Hit</td></tr><tr><td>TTATCCGGCCAGGCGGGAACTGCAGTTCGGAGAGTGGCAGCGCAAAGACA</td><td>10</td><td>0.2277385561375541</td><td>No Hit</td></tr><tr><td>TTAACCTTCACCAGCGTGCGACCCTGGATCTGGTTATTAATGATGGCCTC</td><td>10</td><td>0.2277385561375541</td><td>No Hit</td></tr><tr><td>ATA</td><td>10</td><td>0.2277385561375541</td><td>No Hit</td></tr><tr><td>TTATCCAGATAGTTCGCCAGCTCTTCATTATTGAGTTTTTTCTTAAGCAC</td><td>9</td><td>0.20496470052379867</td><td>No Hit</td></tr><tr><td>TTAATTGGCATCAACACTGCAATCCTTGCGCCTGGCGGCGGGAGCGTCGG</td><td>9</td><td>0.20496470052379867</td><td>No Hit</td></tr><tr><td>TTATCCGGCGTGTAGGCATCGTCATGACGTAAACGGCGATCGGCGGTATA</td><td>8</td><td>0.18219084491004328</td><td>No Hit</td></tr><tr><td>ATCTACCGCGAAGGTTTTACCGGACTGGATCTGGCTTCGTCTGCCGCACA</td><td>8</td><td>0.18219084491004328</td><td>No Hit</td></tr><tr><td>TTAGGGATTAGCGTCTTAAGCTGGCGCGAGGACCAACGTATCAGCCAGGC</td><td>8</td><td>0.18219084491004328</td><td>No Hit</td></tr><tr><td>TTAA</td><td>8</td><td>0.18219084491004328</td><td>No Hit</td></tr><tr><td>ATC</td><td>8</td><td>0.18219084491004328</td><td>No Hit</td></tr><tr><td>T</td><td>7</td><td>0.15941698929628786</td><td>No Hit</td></tr><tr><td>TTT</td><td>7</td><td>0.15941698929628786</td><td>No Hit</td></tr><tr><td>TTATGGCTACTGGCGGTGCGGGTCGCGTTTATCGTTACAACACCAACGGC</td><td>7</td><td>0.15941698929628786</td><td>No Hit</td></tr><tr><td>TTATCCGGCGTTGCAACCTGTGAGCTGTAGATCATATCGGTGATAGCCTG</td><td>7</td><td>0.15941698929628786</td><td>No Hit</td></tr><tr><td>ATG</td><td>7</td><td>0.15941698929628786</td><td>No Hit</td></tr><tr><td>TTAAA</td><td>6</td><td>0.13664313368253245</td><td>No Hit</td></tr><tr><td>TTC</td><td>6</td><td>0.13664313368253245</td><td>No Hit</td></tr><tr><td>TTAGCATGACTCACGCCGGGCGTCCAGTTTTTAGCGACGGGGCACCCGAA</td><td>6</td><td>0.13664313368253245</td><td>No Hit</td></tr><tr><td>TTAGTGCGCTGGTTAGCGTGCGGGATAACGCCTGTCAGGATTATCTCGCG</td><td>6</td><td>0.13664313368253245</td><td>No Hit</td></tr><tr><td>TTATCCATCAGGGAGTTACTGTAAGCGAGAATATATTTATCACTCAATGC</td><td>6</td><td>0.13664313368253245</td><td>No Hit</td></tr><tr><td>ATAACCAGCATCAGCATTGGCGCGTAGAGAAAGGTAAAGCCCAGCAGCAA</td><td>6</td><td>0.13664313368253245</td><td>No Hit</td></tr><tr><td>TTATGCACCGCATCGTGAGCATCTTTCCCCCAGGCGAACGGCCCGTGCTG</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>TTATA</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>GT</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>TTAAGCTGCACCACACCGATACCGAGCGTAGTGGCAATACCGAAGATAGT</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>TTAAATACCGTCGGCGCGTTAATCGGCCCAACTGCGCCACCAACACCAAT</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>ATCA</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>TTGATCGTCAAAACCAACATTGCGACCGACGGTGGCGATAGGCATCCGGG</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>TTATATACCAGGCTTAGCTGGGGTTGCCCCTTAATCTCTGGAGAATAACG</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>TTGAGTTTCAGCAGCCGCGGTTCCGCCAGCACTTTACTGAAACTGCCTTT</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr><tr><td>ATCTACCGCGAGGTTAAGCTGCTGTTCAATCTGGGCGACGCTCAGTTCGG</td><td>5</td><td>0.11386927806877704</td><td>No Hit</td></tr></tbody></table></div><div class="module"><h2 id="M10"><img src="data:image/png;base64,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" alt="[OK]"/>Adapter Content</h2><p><img class="indented" 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" alt="Adapter graph" width="945" height="600"/></p></div></div><div class="footer">Produced by <a href="http://www.bioinformatics.babraham.ac.uk/projects/fastqc/">FastQC</a>  (version 0.11.8)</div></body></html>
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diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/fastQC2/test.fastq2_5pAtccRm_fastqc.zip b/example_of_result/20220120_test_1645716342/fastQC2/test.fastq2_5pAtccRm_fastqc.zip
similarity index 50%
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diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/figures/global_logo_test.fastq2.png b/example_of_result/20220120_test_1645716342/figures/global_logo_test.fastq2.png
similarity index 100%
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similarity index 100%
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similarity index 100%
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similarity index 100%
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similarity index 100%
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similarity index 100%
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diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/figures/plot_motif_insertion_per_fork.png b/example_of_result/20220120_test_1645716342/figures/plot_motif_insertion_per_fork.png
similarity index 100%
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index 1f0f59e02c97edc2ba4be85c45a7fecc2cc449cf..37f48fd363494b5d21c6df20f2cd4b97d92ac7f6 100644
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@@ -1746,7 +1746,7 @@ div.tocify {
 </div>
 <div id="trim-of-the-read-for-the-primer-parts" class="section level3">
 <h3>Trim of the read for the primer parts</h3>
-<p>AlienTrimmer main options: -k 10 -l 30 -m 5 -q 20 -p 0 (Phred+33) / 26 alien sequence(s) / 810 k-mers (k=10) <br />[00:02] 8,932 reads processed: 4,767 trimmed 223 removed <br /><br />AlienTrimmer also removes reads according to quality criteria</p>
+<p>AlienTrimmer main options: -k 10 -l 30 -m 5 -q 20 -p 0 (Phred+33) / 26 alien sequence(s) / 810 k-mers (k=10) <br />[00:00] 8,932 reads processed: 4,767 trimmed 223 removed <br /><br />AlienTrimmer also removes reads according to quality criteria</p>
 <p>Number of sequence before trimming: 8,932</p>
 <p>Number of sequences after trimming: 8,709</p>
 <p>Ratio: 0.98</p>
@@ -2789,7 +2789,7 @@ N
 </div>
 <div id="bowtie2-alignment" class="section level3">
 <h3>Bowtie2 alignment</h3>
-<p>Time loading reference: 00:00:00 <br />Time loading forward index: 00:00:00 <br />Time loading mirror index: 00:00:00 <br />Multiseed full-index search: 00:00:00 <br />3742 reads; of these: <br /> 3742 (100.00%) were unpaired; of these: <br /> 1240 (33.14%) aligned 0 times <br /> 2308 (61.68%) aligned exactly 1 time <br /> 194 (5.18%) aligned &gt;1 times <br />66.86% overall alignment rate <br />Time searching: 00:00:00 <br />Overall time: 00:00:00</p>
+<p>Time loading reference: 00:00:00 <br />Time loading forward index: 00:00:00 <br />Time loading mirror index: 00:00:00 <br />Multiseed full-index search: 00:00:01 <br />3742 reads; of these: <br /> 3742 (100.00%) were unpaired; of these: <br /> 1240 (33.14%) aligned 0 times <br /> 2308 (61.68%) aligned exactly 1 time <br /> 194 (5.18%) aligned &gt;1 times <br />66.86% overall alignment rate <br />Time searching: 00:00:01 <br />Overall time: 00:00:01</p>
 <p><br /><br /></p>
 </div>
 <div id="multiqc" class="section level3">
@@ -2855,29 +2855,29 @@ N
 <p><br /><br /></p>
 </center>
 <div class="figure">
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TAmu1AqUBjogVHzdzeLXwQZ5Af6g3xgF0knpcKmYdyayQi2LuwZELEOPyj089+BMzesrqd8VcQWLlxoYCtN03Ks7AKVR7efTr4dghdU6FLQiVoG1jFQhC1iVmSw+fYwAGoKq9vhtHwMoOUD9xhY9wajIQAAAPCeu9cJAj5Uv3595y1ZWFjYzp07fZ0dz5iY+ZkzZ54/f14sPv74402aNClcuHCFChW8zaX1fPIjXr58uXPnzrGxsfKHpUqVeuihh6Kioq5cubJv3760tDTxp82bN8fExGzYsMHAg+jUERYWVqpUKWPbhoaG6l/54sWLf/zxR/bPV69effv2bU/fhCYUKVKkZMmS2T93OBwJCQkpKSkun2dkZEyePPnMmTPz5893/15cY65evTps2LAcHz/pvfT09G7dum3YsEH+sFixYjExMd26dWvcuHGZMmWcXyo1NXXfvn0///zzZ599lpCQIFa+cOFC8+bNt2zZ8sADD1iRw9x8/PHHI0aMkD8pUaJE9erVQ0JCjh07dv36dfH5Rx99FBER8d5779mZPTd8EosUr8WuXr366KOPyqEyKCioVatWzz77bOvWrcuVK+e8CJOSknbt2rVu3bqvv/766tWrYuUlS5a88cYb06dPd3+US5cudezY8fDhw/KHZcqU6datW/fu3evUqRMVFRUUFJSZmRkXF7d///6lS5f++OOP8sN6//jjj2bNmq1Zs6Z8+fIefTsrinBiYmKHDh1u3LghPgkPDx80aNDAgQMrVqwYFBQkZ2DLli2fffaZKOkOh2PUqFHNmjVr0aKFnmPZENUD4CxZR5FvERiX3Pnz5zt06HDs2DH5w6ioKGccqFu3blRUVHBwcFZWVlxc3L59+5YsWbJs2TL5W2/YsKFZs2Y///yzR3HABv5bTsXObagInGxrqdqmUKFCUVFROf7J4XBcv349+38S3L59u1evXn/88UfDhg1z26099aYPQ1yepfjGjRui5V+wYMF77rnH/fo5joDqEWBNFC9t2rTpxIkTlh4igFueoaGhZcqUcbNCVlZWcnLy7du3HQ6H/PmtW7e6deu2devWWrVqKXIUc2O1naHGr2NydjYECut6YHzbira6lvHVJeFCncrUFIq0Eg1nI7f/EPWIdUHe9CKp5uWnZvvKI3bempnLiiJsXbBV7QK2Z0DE52HWJ7WnbVFdtYvKSz6/WnwycObvnXs+bKAuWLBgzJgxnmb4wIEDhqfQ+PwSdbLo9tPJoiF4c1ubSoU+ahlqGU9ZWoQtYlZksL/Hxv6aQidF/jGJlo8BtHx0UnNc1R5+N7CuTnUfwKMhAAAAsJXVr2QFjBF9OuHh4b7Oi8dMzPzzzz8vSutbb71lSvZsY/+PmJmZ+fDDD8shrlq1aosWLUpPTxfr3L59+5133nHpNBw8eLDVedu+fbt8xN27d3u5wzZt2oi99ejRw5RM5mnSpEnioMHB/887t7/77juPdvXII4+Ibfv16+dmzcTExB07dowYMaJy5couVVjXrl2zsrLcbLt27Vp5/f3792dfJ8c+jqCgoM2bN+v/OkOGDNHzdTIzM59++mn5QMHBwf3794+Pj3ez81u3bk2YMKFEiRLyho0aNZIvbKudOXOmYMGC4ujFixefNWtWWlqa868ZGRlz5syRx3KCg4MPHTpkW/bc80mFYu5BxZU8aNAg7/eWlZXVvn17+XK6//77N2zY4GaTu3fvvv/++3I/Zp5lJCkpqVq1avJRChUq9O6776amprrZKjk5efjw4fLFpmlatWrVkpKSctvEtiIsr6NpWocOHdyXXIfD8f3338vfpUqVKomJibmtbGlUD5izJFffH330kf7MC7Vr1xZ7yK1AWf0tdPLrS87p1q1bLgOihQoVGjlyZEpKiputEhMThw4d6jJsVr16dTdxwGHXtREY5dRhS0Xgk5ZqdiZWoE899ZRcHt2smZmZefbs2dWrV7du3drlB61WrVpGRkaOW9lWb1odW/Q0v3PTr18/seEjjzyif0OPjht4TRQvNW/eXBxiypQppu8/wFqeDodj4MCBYuX69eu7/fb/d6D169e3atXK5Xpo3bq1b49iXay2OtQETEy2LVDY0wOjSCs6N97UMnYGGS8Z/pryPxJpmjZ//nwDR5cvm2HDhuW4jiKtRIuyobNBYk+Qt79IelPKdLItbNpzg+mwvqXkX0MSvg22NtyM2FMdKxJmHfb+oOp8axmVsn52DpwFTOeebUVsypQp2b+UpmkHDx7U/6WcXB59K+T2QytyiVp9+ymYOARvT2szRzY0CJ2oZahldLKoCJvezM6NWZHB0ttDH9YUSrXD9aPlI6PlIygSNvPkEgBzK3c29KsE2MB6jhg2zc6GYVMAAAAYFpy9wQdAHfILpuRJqsjR3Llzd+3aJRZbt269c+fOHj16yF0exYoVGz9+/I4dO+Tng37xxRenT5+2Na/+ac6cOSLduXNnebbJvHnzLDpoeHh4o0aNPvjgg2PHjo0ZM0bu11i2bNnMmTOtOKjD4RgwYID8cl1TTJw4ccGCBWIxPDz8119/nTlzpvvH3RUvXnzYsGHr16+PjIwUH+7cuVMeirDaiBEjxNkoVqzYunXrXnzxRTFrKCQkpE+fPhs3bixdurTzk6ysrGHDhtmWPXjko48++uWXX8RikyZNDhw40LJlSzebFCxYcNSoUV9//bX4xOFwDB482M0mgwYNkt++VaFChf37948ZM8b966mLFCkybty4PXv23HvvveLDEydOvP766262ys70Ipyamvr555+LxZo1ay5YsCDPB1X27dv3+++/F4tnz5795JNPzMqS9zhLOVLkWyiSDS+98sorcvuqfPnye/fuHTt2bFhYmJutwsPDJ02atGPHDvmpn8ePHx80aJCFeVWVRQ0SeyqCfCs4OLhy5codO3Zcu3btsmXLChUqJP504sSJ3NrM9tSbgRFbvBRgTRRvZGZmDh48OMeH7psoP7Q881SkSJHHH3983bp1Lnev69atk3sw/OIoeigValSOybnxbaAw3AOj1O9uOsWDDPIDT4N8YBdJF0q1rzzFrZmMYCv4ZEDEdPyg0M9/B870sKie8kkRk0fbFy5c6GmeFy9e7EwE6ou8jN1+Cj4ZghfU6VLQiVoGpvOyCFvElMhg5+2hv9cU9rTDafkYQMsHOjGwbkB+Hg0BAACAuZiYCigtJSVFpPPsHITco1quXLmFCxdGRETkuGZ0dPSMGTPEYnp6eo5PZoLs6NGjBw4cEIvPPvtsjx49xOLatWuvXbtmaQacD+VasmSJ3AX89ttvx8bGmnWIokWLivTRo0c//PBDs/asadpff/01YcIEsRgREfHbb79lf+hmburXr79q1So5h//5z39SU1NNzGFujh07Nn/+fLE4duzYhg0bZl+tRo0a06ZNE4urVq3asWOHDdmDRy5fvvzOO++IxVq1aq1cuTI8PFzPti+88EKfPn3E4r59+1weiCjMnz//22+/FYtVqlTZtGnTQw89pDOTtWvX3rRpU8WKFcUnX3/99dKlS/Pc0LoivHbtWrlG/v7774sXL65nw169ej355JNice7cuWZlyTDOknuKfAtFsuGN2bNny0d3xoGaNWvq3LxBgwabNm0qX768+OTbb7/11di//SxtkNhTEcDpqaeeGjdunPyJ3KaSP7Sn3gyA2OKlwGuiGPPXX3/NmjWrQYMGn376qaUHCuyWpwH9+/eXb6I1TVuzZo2fHsUNZUONajHZhWqBwtMeGGV/d+/5UZBBfqAzyAdwkRRUC5sGcGsmI9jmyIYBEYvwg0I//x04c8/SespXRezRRx8tUqSIM+3p9IxDhw4dP37cmdb/+/ovnbefgs+H4AWfdynoQS0Dq3lahC1iVmSw8/YwYGoK69rhtHwMoOWDPDGwbhijIQAAADARE1MBvxEUFOTrLCjtr7/+km/gR44cWbJkSTfrd+3atXv37mLxp59+sjBzAUHuay5WrFinTp3kvu+MjAzxyDdLderUSX4Y4a1bt8aMGWPWzhs0aPDUU0+JxXHjxskPBvPSe++9l5SUJBZnzJjxyCOPeLSHJk2aTJ06VSzGx8fPnj3brOy5sXjxYofD4UxXrFjRzTvrnnvuuTp16sgbWp45eGj69Ol37951poODg7/77rsSJUro3/zzzz+XuwhzfDJoZmbm8OHDxWJoaOjSpUsrV67sUT4ffPDBRYsWhYSEiE+GDRuWlZXlfivrirA8y7pKlSrR0dH6t33ppZdE+siRI5cvXzYlS4ZxltxT5Fsokg3DMjIyRo4cKRZDQ0OXLFlSpUoVj3ZSvXr1hQsXynFg5MiRmZmZpuVSYZY2SGyoCCB788035SnZGzduzMjIkFews97099jipYBsougXHx8/ZMiQLl26VKlSpWzZsv379z906JDVBw3slqcx48ePlxctepSPPUfJjcqhRqmY7EKFQJGd/h4YlX93b/hdkEF+oCfIB2qRlKkZNj3CrZlAsHXP0gERK/CDwiP+O3DmnnX1lA+LWNGiRcUMpRMnTsjTpfIkDxe6zHsMVHnefsoUGYJ38m2XQp6oZWAPj4qwRcyKDHbeHgZYTWFFO5yWj6do+UAPBtaNYTQEAAAA5mJiKoAAsWfPHjF3Ljg4uFu3bnlu8sILL4j08ePHExMTrcpcQJBfU9a1a9ewsLCGDRtWqlQpxxUs9cILLzz22GNice7cuXLvrZc+/fTTYsWKOdN37959+eWXTdnt8ePHv/rqK7HYo0eP3r17G9jPP//5T/n1cStXrjQhc3lZtmyZSPft21fuUcpOLlbyhlBBcnKy3NH50ksv/eMf//BoDxEREV27dhWLP//8c/Z1Fi9efPbsWbE4atSo+vXre55ZrVGjRkOGDBGLJ0+e1HPBW1SEr169KtLyA//0kOOVpmkqvNOAs+SGIt9CkWwYNn/+/IsXL4rFUaNGNWjQwMB+Hn30UTkOnDlzJv888sCicmpPRQBZcHCw/I8FSUlJV65ckVews97099jipYBsouj3119/TZ06dcWKFefOnbPniPmh5WnAAw88EBYWJhYteueJPUfJjcqhRqmYnJ3PA0WOdPbAqPy7e8PvggzyAz1BPlCLpAs1w6ZO3JrJCLZ5snRAxHT8oNDPrwfO8mRRPeXbItarVy+R9ujVYaJTNyIiom3btvo39F953n7K1BmC13zdpZAnahnYw6MibBGzIoPNt4cBVlOY2w6n5WMALR/oxMC6AYyGAAAAwFxMTEXgSElJWbp0aZ8+ferVqxcVFVW0aNHatWt36dJl+PDh8n1UntLT05cuXfryyy83aNCgTJkyBQsWLF68eKVKlZ544olx48ZduHDBuq/gvbS0tGXLlr3++uuNGjWqVKlS0aJFCxUqFBUVVbt27d69e8+YMUP/4IH95yElJWXRokU9e/asVatWZGRkREREnTp1evXqtWLFCj0PIDx69KhI165du0yZMnluUrduXXlR7pOFi+3bt585c0Ys9unTx5mQn+62efPmS5cu2ZOfDz/8UKSTkpLmz59v1p7vu+8++Vmwv//++zfffOP9bn/44QfxkregoCCXx83qFxoaKk+6tuHxnJcvX967d69YlN8znCN5hdOnTx85csTLDNgfi0wMpKqZPXt2QkKCWHz77bcN7KRdu3YiffXq1ZMnT7qsMHnyZJEuU6aMsaM4vfvuu5GRkWJx2rRpeW5iURFOSUkRaU+HHkuUKFG+fPnSf1PhfY+cJTcU+RaKZMOwKVOmiLS5cWDSpEle5cx/WFRO7akI4MLlpiM+Pl5etLPe9PfY4qWAbKKoLD+0PA0IDg5+6KGHxGJycrL/HiU3iocadWJydsoGCj09MIr/7ob5XZBBfqAnyAdqkXShbNjUg1szGcFWD+sGREzHDwr9/HfgTA+L6infFrEnnnhCvPFJ//SMo0ePikH8Ll26FCpUyMOc+iv3t5+CakPwvu1SyBO1DGyjswhbxMTIYPPtYeDVFCa2w2n5GEDLBzoxsG4AoyEAAAAwFxNToZAFCxYE/b70ZwkAACAASURBVE30myQlJQVJ7t69m+O2s2fPrlKlSvfu3efNm3fw4MH4+PiUlJQjR46sWLFiwoQJVatWfeaZZw4fPpxnHubOnVupUqXu3bvPnDlz//79cXFx6enpiYmJFy5c+Pnnn0eOHFmlSpWBAwdmfwqaN5l3cfz4cbGJnOfy5cuLz7ds2eKylcPhmD59+v3339+tW7dPPvlk165dFy5cSElJSUtLi4+PP3LkyPz581999dXy5cu//fbbd+7cUe08LF68+IEHHujVq9fixYuPHj1669at27dvHz58eNGiRV26dKlaterWrVs1TUtOThb7kXsANU2Li4sT6WrVquVxljVN0zT5eZ+apqWlpenZKn+aO3euSEdFRbVu3dqZ7tmzp/jc4XAsWLDAnvw0btxY/pUXLVpk4s5fffXVxo0bi8UhQ4Z4PxFx1apVIv3EE09UrVrV8K5Gjx69/29//PGHeFGwRfbv3y/SYWFhLmMw2VWuXFmeFi5vboDNscjLQGpiRWAR+fF7TZo0uf/++w3spF27du9J0tPT5b+ePn16z549YnHAgAEFCxY0nOEiRYr069dPLG7cuPHy5ct5bmVFEa5SpYpInz592tMHGVy8ePHa3+Qn7PoQZyk3inwLRbJhzIkTJw4cOCAWvY8DL774oljcu3evR0+c8WtWlFMbKgLkSW5C2Fxv+nVs8VKgNlH0K1my5KCcePqYfP3yScvTAPlfuMqVK2fFIWw7So78K9T4MCbnyLeBIjd6emD863fXSYVLAshRnkE+IItkjtQMm3pwayYQbHWydEDERPyg8Ij/DpzpZHo95fMiVqRIkU6dOjnTp06d2rdvn54DySFLHlbOb3L79wzVhuA1n3YpuOfzIoD8LM//sDKXiZHB5tvDwKspTGyH0/LxlM/DfuBdz4GNgXWP+Lx8af7crQcAAIAcMTEVfi8tLa1r164vvPCCPC/RRWZm5oIFCx555JHffvstt3UcDserr7767LPPun9KXFZW1pdffvn4449nnwflQykpKd27d3/ttdfyvK9LS0ubNGlSx44dc+s5tf88OByOV155pWfPnm76QM+dO9eiRYsZM2a42c/NmzdFumzZsnoOLT9lMCgoyFgPQn7gLEFi8emnny5QoIAz3ahRowoVKog/zZs3z7ZcPf300yK9a9cuE/ccHBw8c+ZM8R1v3Ljx5ptverPD2NhYuY/yn//8pzd7K1myZD1JaGioN3vL07Fjx0Q6OjpanBY3GjVqJNLHjx83dlz7Y5GJgVRNDodj8+bNYlEuQR4pU6bMaEnNmjXlv27YsEFe7N+/v7GjCAMGDJAX//jjjzw3Mb0Ia5r24IMPinRmZuZLL72kyACPYZyl3CjyLRTJhjG///67vOh9HHj55Zfd7D+AmV5O7akIkN2hQ4fkxdKlS4u0zfWmX8cWLwVqE0W/e++9d3pOLCrC+afl6SmHwyE/D1u+m/a7o+RG8VCjTkzOkW8DhRt59sAo/rsbo8IlAWSnJ8gHZJHMkbJh0z1uzWQEW/2sGxAxET8o9PPrgTOdTK+nVChi8vwKnZNzFi9e7EwUL168bdu2nmTQv7m5/RQUHIL3bZeCeyoUAeQfeoqwRcyNDPbfHgZeTWFKO5yWjwEqhP3Au54DGAPrHlGhfPlptx4AAAByw8RU+Lf09PSuXbv++OOP8oflypVr06ZNTExMgwYNgoP/7yJPTk7u1KmT6AJwMXHiRJd5jyVLlnz44Ye7dOnStGlTl4mOu3fvfu2118z7Ht4aMWLEsmXL5E8iIiLq16/fqVOn9u3b165du0iRIvJff//997Fjx+a4K/vPw+uvv/7FF1/In4SEhNSsWbN169b169cvXLiw88PMzMzBgwfLD6NyMXny5Kt/mzBhgp5D79y5U6QrVKjg8gJVCGvXrpUnfvfp00ekg4KCunfvLhb37NkjD1ZZSn5uVkJCwqlTp0zced26df/3f/9XLM6ZM+fXX381vLfVq1fLi82bNzeeM9v9+eefIv3AAw/o2USe433ixAljx7U/FpkYSNV06NChhIQEsSiXIBPJE8aqVq3q/Yh1jRo15J9706ZNerYytwhrmta0adOQkBCxuGrVqhYtWsilwx9xlnKkyLdQJBvGmB4HqlatWr58ebHoMkwS2Mwtp/ZUBHDhcDi2b98uFkNCQuR6zeZ6069ji5cCtYmirHzV8vTIqVOnUlNTxWKLFi1MP4RtR8mNyqFGqZicGzUDRZ49MCr/7oYpckkALvQE+YAskrlRM2y6x62ZjGCrn6UDImbhB4V+fj1wpp+59ZQKReyJJ54oWrSoM71w4cI81z9+/Pjhw4ed6ZiYmEKFChnKqf9xf/spKDgE79suBfdUKALIJ3QWYYuYGxnsvz0MvJrClHY4LR8DVAj7gXc9BzYG1vVToXxp/tmtBwAAgNwwMRUKad269ea/ia6xsLCwzZKCBQvKm0yYMEHuvmnQoMH69esvXbr022+/LV++fO/evRcvXhw0aJCYnpqWlvbCCy9kfxtebGzs+++/LxarVKkyb968uLi4nTt3/vjjj5s3b46NjV22bFmVKlXEOt99953cx2cg87mpWLGi2EQ+4tKlS8XnderUEZ8fO3bss88+kzf/5ptvrl27tm/fvp9++mnNmjWHDh26evXqp59+GhkZKVb79NNP09LSfH4eVq5cOX36dLFYoECB4cOHX7hw4ciRI2vXrt23b9+VK1cmTZrknDKamZnZr1+/3M5bREREmb+Fh4fnfoL/f5mZmZ988olYfPTRR/PcJN+aO3euSFepUsXlXPXo0UNetO2JrfXq1ZMXd+/ebe7+R48eLU+wHDhwYEpKirFdyQ/UfOihh6KiorzNnI3kAi7PC3JDXs3YxFT7Y5EpgdTEisAK27ZtE+mQkJC6detacZQtW7aIdNOmTU3Zpxxz9D+u2MQirGlatWrVnn/+efmTzZs3161b94knnvjhhx8SExMN79m3OEvZKfItFMmGMVu3bhVps+JAs2bNctx/fmBiObWnIoCLjz/++MiRI2Lx4YcfLlasmFi0ud7069jipUBtoigrv7U89Rs6dKhIR0VFPfPMM6Yfwraj5EblUKNUTHZDwUCRZw+Myr+7YepcEoBMT5APyCLphoJh0z1uzWQEW/2sHhAxBT8o9PPrgTOPmFhPqVDEwsLCOnfu7EyfPn1679697teX3y0mv3Ms4Lm//RQUHIL3bZeCeyoUAeQTOouwRcyNDPbfHgZeTWFKO5yWjwEqhP3Au54DHgPrOqlQvpz8rlsPAAAAuWFiKhRSunTppn8LCgpyfhgSEtJUIj7XNO3o0aPjxo0Ti927d9++ffvjjz8ur1OuXLnp06cvWLAgNDTU+UlKSsqIESNcDr1w4cI7d+4401FRUWvXrn3mmWfk58YFBQU99dRTK1asEC/VzMrKkt/U6mnm3QgLCxObiCdvaZrWqFEj8Xnx4sXF519++WV6erozXaxYsTVr1vTr1098X/H5v/71r+XLl4vPb9++Lb8v1CfnISUl5dVXXxXbFi1a9Pfffx83bly5cuXEh5GRkUOHDt2yZYvzKycnJ+s5h3pMmzbt9OnTYlEeZYEsNTVVfo2k/ERGpyZNmsg/mW0TU8uXLy8XEPmxkaYICwuT3+V79uzZMWPGGNvVX3/9JdK1atXyNmf2unXrlkjLP7Qb8mo3b940cFD7Y7IpgdTEisAKV69eFenKlStb9I7o2NhYkf7HP/5hyj4bNmwo0hcvXtS5lYlF2GnMmDGlSpWSP8nIyPj555+fe+650qVLt2rV6sMPP9y3b5/D4fDmKDbjLOVIkW+hSDYMuHLlikibFQeio6NFWo5m+YGJ5dSeigCyVatWvfPOO/InLuPQ9teb/htbvBTATRQ15beWpx4ZGRmTJ09evny5+OSDDz4w/Ynp9hwlT2qGGgVjcm4UDBR6emDU/N29oc4lATh5FOQDr0i6oWDYdI9bMxnBVj+rB0RMwQ8K/fx64MwjJtZTihSxXr16iXSerw5bvHixM1GsWLH27dt7nkG/lOftp5NqQ/CKdCm4oUgRQMDTWYQtYkVksP/2MMBqClPa4bR8DFAk7AfY9RzwGFjXSZHypflhtx4AAAByU8DXGQCMmzRpknhVXYUKFWbPnp3bm+h69Oixffv2qVOnOhdnz5795ptvyk81k59y1KdPH/lJPLLatWs/+eSToh9h//793n8L7+3atUuk33rrrRo1auS2ZosWLR5++GHxmqnsb461+TzMnz9fvhGdO3dubg9hatCgwQ8//BATE2PsQNn9+OOPw4YNE4vt2rUz6zbbJ1avXi2/OlK/N9544/XXX3e/zsqVK+UHJfbu3dtlhaCgoG7dun366afOxWPHjh04cMDlqYEWiYyMFHOVjU2AdK9t27Z9+/b94YcfnIvTpk3r06ePga8m9zK7dPqrT54NrvNRoHK/vLEnmdkfk00MpMqKj48X6ZIlS1pxiKSkJPkVsmY96bNMmTIifevWrYyMjAIFdLVgzSrCThUqVNixY0enTp2OHTvm8qe0tLQNGzZs2LBh2LBh99xzT9u2bdu3b9+2bduyZcsaO5alUd2F/54l6yjyLfz0kktMTLQiDsj7SU5OTk1N9fnYjz+WUxsqghzZea4UERsbe/To0alTp65Zs0b+vGLFivJzeXxSbyoS4mwW2E0UNeXDlmeOMjMzY2NjL1y4cOTIkSlTppw8eVL8afTo0QMGDPAqr6YexdxYrVSoUTkmu6FgoMizB0ap3917ql0SNhs8eLDccarTpUuXPFpfkVaigWz88ssv1apVMysD7hkO8gFWJPOkYNh0w1e3ZuYypQjn82BrgEcDIvaHWRV+UMWjugEBXCn7fODM7zr3VChiTh07dgwPD09KStI0beHChRMnTsxtzZMnTx44cMCZjomJMTzFUZF2Y5503n4KKgzB29NxYQoVigC1jJNf1DIGeFqELWJFZLD/9tD+msJq3v9jEi0fWj76+UvYVJa/D6zbQJ3y5eRf3XoAAADITYAMxSEfSkhIkJ9ENXny5CJFirhZf8SIEf/9738TEhI0TXM4HHPnzpVvYOQ+oJo1a7rZT7du3ZzdDZqmVapUyVjmzSW/lqpt27buV65fv76YTyVeSCjYfB6++uorkX7qqafczzvt3Llzu3btfv31V2PHErKysiZMmPDee+9lZWU5P4mMjPzoo4+83K1vpaSknDt3zsCGevpM586dK9L16tXL8el9PXv2FH3fmqbNmzfPng6C4sWLi2mBztJtumnTpq1evfrGjRuapmVkZPTv33/79u3BwZ69b1wuWTq7q2JiYg4dOqRnzaefftpN16f3REnXNE1nz2nhwoVF2thbju2PySYGUmVdv35dpCMiIqw4hNwzq5nXOeuynxs3btxzzz06tzWlCAsPPPDA9u3b33333dmzZ+cWP+Pi4ubMmTNnzhxN0+rWrdurV68BAwZ42pNraVTPzk/PkqUU+Rb+eMnJoUYzLw64jNFev369fPnypuzZMH8spzZUBDmy+VzZYOPGjbkNCTscjvj4+BzbP4ULF/7hhx/kZpKv6k1FQpydAr6JoqB80vLcv39/UFCQp4eIiIiYOHHiwIEDda5vz1FMj9W2hRp/j8luqBYo9PTABFIVo+AlYadr165du3bN6qMo0ko0kI309HSzjm5pkA+kIqmHamHTDV/dmpnLlCKcz4OtAR4NiNgfZlX4QX0b1a0QwJWyzwfO/K5zT4Ui5lS4cOHOnTs739F39uzZ3bt3yy9HkokHy2revW9QkXajWbefgg1D8PZ0KdhDhSJALWNMoBZhi1gUGWy+PbS/prCa9/+YRMuHlo9+ioRNv+bXA+s2UKd8CX7UrQcAAIDc0HqDv1qxYkVqaqozXbdu3aefftr9+iVKlBg8eLBYXL9+vfzXe++9V6T37t3rZj+9e/f++W/jx4/3ON8W+OWXX4797ZFHHnG/ssPhcPNXO8/DlStXtm/fLhaHDBmS5ybeP4nwzz//fPzxx0eOHJmRkeH8pFChQsuXL3fzdsR8LiEhYfXq1WKxT58+Oa7WrFkz+cFX8+fPd3+lmUV+M6c8f9JEUVFR4mXLmqbt2rVL7uXXSe7+Cw0N1bPJlStXzunjMgXIdPIYjM5BF+8nptofk00MpMqSx0jCw8OtOMStW7fkRZ2v2M1TZGSkvOjRNW9KEZZFRER8/PHHsbGx3377bfv27d2/s/HgwYMjR46sUKFCv379Tp065c1xLcVZypEi30KRbOhnURxw2c/t27dN2a0fMaWc2lAR5BOpqam5NczOnz+fY+OnaNGiCxYsaN68ufyhD+tNv4stXsoPTRTV5M+Wpx7R0dHHjh2z+p877TlKnuwJNQEQk3OjWqDQ2QMTMFWMgpcE4ORRkA+YIqmHamHTDW7NBIKtp2wYEPEGPyg84tcDZwZ4X08pVcR69eol0vKTxF0sWrTImQgPD2/fvr2hDCrErNtPJ2WH4BXpUshOqSIAf2RuEbaIpZHB5tvDAKspvG+H0/Kh5QM7MbDunlLly8mPuvUAAACQGyamwl9t27ZNpFu0aKFnE/mZVUeOHBEvzNQ07aGHHhLpr776Sn4KnfoefPDB6n8LCQlxs6bD4dixY4ebFew8Dzt37hTpihUrNm3aNM9NOnbs6L571I3k5OR33nmnXr16mzZtEh86H3Co8/rJn5YsWZKWluZMBwUFPfPMMzmuFhwc3K1bN7F4/vx5uYRaJyUlRaTN6ijJrl+/fo8//rhYHDFixMWLFz3aQ/HixUXa+XwvP2JggFPexOFwiHng+tkfk00MpMqSu0rlsmMil8cEJiYmmrJbl9x62ufrfRHOLiws7IUXXlizZs2NGzd+++23oUOH1qtXL7fHTt+9e/e7775r3Ljxxo0bvTyudThLuVHkWyiSDT0sigMuM1FLlChhym79i/fl1IaKADl65JFHdu3aFRMT4/K5z+tNP4otXvL5qc6RFZWvOvJtyzNPe/fuffbZZ48dO2bubn1yFJ1UCzXKxuQcKRUoPOqBUe13N0DNSwLQDAX5ACiSOikVNt3g1kwg2HrKngERw/hB4RG/Hjgzxst6Sqki1qFDBxGFcpuecebMmX379jnTnTt3tvN9g4rI7fbTSdkheKW6FGRKFQHkB+6LsEVsiAy23R4GWE3hfTuclg8tH9iMgXU3lCpfgr906wEAACA3TEyFv5LnBT388MN6NqlevbpIp6amXr58WSw+9thjIp2VlfXss88+/vjj8+fPlx9a5u8OHjzYu3dv9+8etPM8yBNTmzRpomeTggULVqpUycCxli1bVqNGjYkTJ6anp4sP69atu2vXrh49ehjYoWp69OjhMGT06NHu9yxPCGzWrFnFihXd5EFenD9/vpdfSg95morLk7fM9cUXXxQqVMiZTkpKGjRokEeblypVSqTj4+PNzJn15Kc/3r17V88md+7cEemCBQsWKFDA04MqG5P1BFJlydehRWdSPoRm3piKy4P05EfA6uRlEXajcOHCbdq0mTRp0v79+69cufL9998/99xzZcuWzb7mjRs32rVrJx6T6Z51Ud0NvztLNlPkW6h/yVkUB1z243IUn/DHcmpDRZAjn5wr3woKCipZsmStWrUGDhy4du3abdu21ahRI/tq6tSbioQ466hzql1YV/n6XD5peYaGhpbPi8sAv6Zp69evb9So0aFDh3RmyZ6j2BCrfRVq/C4mu1AnUBjrgfHfKkbZS8IezteteKpy5coeHUWRVqKBbNSqVcuso9sT5AX/LZL6qRM23fDVrZm5TCnC+TzYGuBRdWx/mFXhB/VtVLdCAFfKPh8487vOPRWKmFC4cOHOnTs70+fPn5cH/QW5IdGzZ08v8qhKuzFPOm8/newZgre5tWkpFYoAtYyTX9QyBnhUhC1i5z/nWH17aHNNYTXv/zGJlg8tH/38JWyqz08H1m2gVPmS+UW3HgAAAHLDxFT4qzNnzoh0UFDQDh3i4uLkJ71du3ZNpFu2bCk/Uk7TtN9//713795RUVFNmzYdPnz4mjVrzHo+kA1SU1P379+/ePHiCRMm9O/f/7HHHitRokS9evUWLFjgfkM7z4P8WKM6dero3MpN32tuR+ncuXO3bt3kwwUHB7/11ls7d+6sXbu2R3vLb2JjY+VnH/bp08fNyo899lhUVJRYXLhwYWZmpoWZ0zTt/+36sfTladWqVRs5cqRYXLFixdKlS/VvXrp0aZGWp8S7sWvXLjf9iWvXrtV/dC95OTHV2JNlVYjJhgOpsuS+RYsew1msWLGCBQuKRbme9YY8NlOqVCn5EDp5WYR1KlOmTN++fWfPnu0MngMHDnTpz01LSxs4cGBCQoLphzYFZ0k/Rb6FItlwYUMccDlEvuJlObWhIsgnOnTo4H7oNysr6/r164cPH54xY0br1q1z24+a9aaascVLap5qza7K1yfyScuzVq1aF/Ny8+bNuLi4jRs3tmzZUmyYmJjYuXNnneXInqPYzMRQE9gxWVMpUHjfA+NfVYyylwQCjA+DvH8VSf3UCZtucGsmEGw9ZduAiDH8oPCIXw+cGeZNPaVaEevVq5dI5/jqsMWLFzsTRYsW7dChgxd5VIVZt5+ajUPwgdSloFoRgN8xsQhbxIf/nGPR7WEg1RTet8Np+Wi0fGA7BtZzo1r5EvyiWw8AAAC5YWIq/FJmZqY8Jen5559/RIfmzZs7HA6xlctN4/fffy/3IzhlZGRs3bp1woQJHTt2LFGiRIsWLaZMmRIXF2fptzNs586dr732Wp06dcLDwxs0aNCzZ8/hw4fPmjVr06ZN+h/dZNt5kLOk/7VXHr0x9csvv6xZs+bKlSvlD1u0aLFnz56pU6eKZywhN/Pnz8/KyhKLr7zySlDuChQoIHdV/PXXXxs2bLA0e7GxsUlJSWLR6gef//vf/65Zs6ZYHDx4sPxYRPfKlSsn0nv27ElLS/MyM3bOk5cnpiYnJ+vZRF5N3twjvorJpgRSNcmjHefOnUtNTbXiKPfee69Im/Vq2f3794t0jg9q1cObIuypoKCgFi1azJgx49y5c4MHDw4O/r/29o0bN8aOHWvRcb3HWfKUIt9CkWwIVsSBffv2ibRcq+ZD3pRTeyoCeETZelNTL7Z4SdlTbWfla6d83vJ0ERUV1aJFi/Xr18sD6ufPn//vf/9ryv7tPIrplAo1yl5RKgQKc3tglPrd3VD2kkA+ZGmQ95ciqZ8KYdM9bs1kBFv9bB4QMYYfFPr59cCZN7ypp5QqYh06dChevLgzvWjRIvl/MDRNO3fu3O7du53pTp06hYWFeZ3TgKLaELy/dCkoVQQA06kQGcy9PQyYmsKUdjgtHydaPrAZA+u5Uap8ydTv1gMAAEBumJgKv3Tz5k2Xm3wDXDp6ihQpsmDBguXLlzds2DDH9TMzM//444+hQ4eWL1/+vffeS09P9zIDJrp48WKvXr0aN248ffr0w4cPy/2Vsho1akRHR7vflW3nQZ7ipf+dijqnIiQlJfXp02fgwIFy/2ClSpUWLly4cePG+vXre5TVfGvu3LnebD5v3jyzcpKjAwcOyIu5XbFmKViw4MyZM8Vbl2NjY9955x2d2zZt2lSkU1NTve/T+euvv7zcg35yX9uVK1f0bCKvZvjB7fbHZBMDqZrq1asn0hkZGfIsL08NHz487G/h4eFyfdqkSROR3rJli+FDyDZv3izS8rfwiDdF2LDw8PBPPvlk6dKl8gvbP//884yMDKsPbQxnyTBFvoUi2ZBrPSviQLNmzUzZp5/yppzaUxHAI8rWmzJFYouXlD3VPql8bZDPW545CgoKGjVqlPywrV9++cXE/dt5FCuoEGqUvaJUCBQW9cCo8Lu7oewlgXzL6iCveJHUT4Ww6R63ZjKCrX42D4gYww8K/fx64Mwb3tRTShWxQoUKxcTEONMXLlzYuXOn/Ffx0jBN03r27OldHgOQmkPw6ncpKFUEANMpFRlMuT0MmJrClHY4LR/nIi0f2IyB9dwoVb5k6nfrAQAAIDdMTEX+leNtXkxMzK5duw4ePDhq1KhGjRrJT4AT0tPTx4wZ07hx49jYWOuzmbfTp08//PDDixYtcvm8cOHC0dHRvXr1Gjly5IIFC86cOXP06NEWLVro2acN56FgwYIirfM1jJqmXb9+Pc91bty40bJlS7njNTQ09L333vvzzz/pANLv+PHje/bs8WYPS5cutbQzRe7pK1Wq1P3332/dsZyaNm06YMAAsThjxoxt27bp2bB58+by4rp167zMyZkzZ7zcg34PPvigSF+6dEnPJnJMqFq1qjdHty0mWxFIVfPoo4/KgXf79u2Gd7V37947f6tQoYK825YtW4r0iRMndF4zbpw/f/7s2bNisXPnzoZ3ZbgI79ixY9XfDJS+Ll26DB48WCzevXv39OnTnu7ENvn8LCnyLRTJhmGmx4GzZ89euHAhx/3nT4bLqT0VATxiZ73p77HFSwHZRFEZLc8cFSxYcNCgQWLx0KFD5u7fzqPkxq9DjcpXlM8DhfseGL/+3d1Q+ZJAvqUnyAdqkfSIz8Ome9yayQi2+tk/IGIAPyj08+uBMy8ZrqdUK2LysPvChQvlP4nhtqJFi3bs2NGLPAYglYfgfdulkCfVigBgIosig89vDwOjpjClHU7LRyzS8lFNYmLiOkl8fLyvc2QyBtZzpFr5kinerQcAAIDcMDEVfikyMlJ+MFtycrLDc0899VRu+69Tp87777+/Y8eO69evr1ix4q233oqOjpaPqGnavn37Xn31VQu/pD53795t3769/Cy0ihUrTpo0afv27bdu3dqzZ8+CBQvGjh3bq1evKlWqeLpzS89DZGSkSOuZbup07tw59yskJia2atVK7rStUaPGjh07Ro8eHRYW5nk28y+XJzK2bdu2kw7Vq1cXm9y8eXPNmjXW5XD+pIABJgAAIABJREFU/Pki3ahRI+sOJJs4cWLZsmWdaYfDMWDAAD0v6qxUqVLFihXF4qxZs3J7G6dOv/32mzebe6RatWoiLfciuXH+/HmRli8Jw6yOyZYGUnWEhYU1btxYLBp+6mpWVpbc5Vq7dm35r4899pi8+NVXXxk7ivDll1+KdEhISPv27b3Zm7EiPHHiRBHlZsyYYeC4zz33nLz4559/GtiJbVQ+S/Ls9MzMTANHkbfKPtddkd9akWwY5jJx1Ps44HIScpyYavW1oRpj5dSeigAesbPe9PfY4qWAbKKojJZnbuQH98TFxVn0Djp7jpIjvw41il9Rvg0U7ntg/Pp3d0PxSwL5Vp5BPlCLpKe8CZtW32ByayYj2OrnkwERT/GDQj+/HjjznrF6SrUi1r59++LFizvTixYtcjgczrT8GrEnn3yySJEiXuYzwCg+BO/DLoU8qVYEABNZFBl8fnsYGDWFKe1wWj60fJR14sSJNpIdO3a4WVl8a/dUG7hnYD071cqXi8AbNgUAAMgPVP+PWyBHISEh4m5f07SbN29adKDIyMjOnTtPnTp1z549Fy5cmDhxonzc5cuX//LLLxYdWqd58+bJD6UbPXr0yZMnhw4d2rhxYxMfsGTFeShRooRI63/cZp4TUwcMGHDgwAGx+Pzzz+/du7dBgwaeZg9yl8qDDz7466+//qSDS3e2/N5ac+3evfvYsWNisUePHhYdyEVkZOQnn3wiFg8fPjx58mQ9Gz799NMife7cuVWrVhnOw7lz5/bv3294c0/JE1P37t2rp59Rnhkub+49i2KyPYFUBa1atRLpPXv2yNFSvy1btty6dUss/uMf/5D/Wr169bp164rFmTNnevPY5tTU1JkzZ4rFpk2bynWHAcaKsHxQY+8JqVOnjjyV+tq1awZ2YhuVz1KpUqVEOiEhwcBR5Gd83nPPPS5/VeS3ViQbhlWtWrV+/fpi0aM48Nprr82aNUv+JCkpySUOlC9fPvuGVl8bqjHcILGhIoBH7Kw3/T22eCkgmyiKo+WZo0qVKol0VlZWUlKS6Yew7Sg58utQo/gV5cNAkWcPjF//7m4ofkkg38ozyAdqkfSUN2HThhtMbs0Egq1OvhoQ8RQ/KDzivwNn3jNWT6lWxAoVKtSlSxdn+uLFi+If7pcsWSLWkd8tBifFh+B92KWQJ9WKAGAiiyKDz28PA6CmMLEdTstHLNLy8V93797Vs5pqA/cMrGenWvlyEZDDpgAAAAGPianwVzVr1hTpEydO2HDE8uXLv/322wcPHixZsqT4cMuWLTYc2o3Zs2eLdO/evd977z2rp1GZdR7kR0Bt27ZNzyaZmZnuX9i4ZMkS+WF1r7zyyrffflu4cGFP84Zdu3adOnVKLD777LM6N3zsscfuvfdesbhixYrk5GSTM6dpmqYNGzZMpIsVKyb34VqtZ8+eTz75pFgcO3asfK5yM3jw4AIFCshbGXssnKZp48aN0/kUOlM0adJEPH/u1q1becbba9euyW9Mbdq0qUUZMzEm2x9IfeXFF18MDQ0Vix988IGBnXzzzTfyYvbXjw8ZMkSkr1696k3/4Pjx4+VXar/yyiuGdyUYKMIPPPCASMsjT/o5X+0uFu+77z4DO7GTsmdJPBZR0/Gsiuzi4+PlMQx5b06K/NaKZMMbLnFgypQperb6+uuvp0+f3r9//7feeks8J/jDDz+Uh2refvvtHLe1+tpQkLEGiT0VATxiW70ZALHFS4HXRFEcLc8cyTcvmqalpqb671Fy5O+hRvEryleBIs8eGH//3d1Q/JJA/pRnkA/gIukpw2HThhtMbs1kBFs9fDgg4il+UOjnvwNnpjBWT6lWxHr16iXSCxcudCYWLVrkTBQpUqRjx46GcxiQ1B+C92GXgh6qFQHAFNZFBhVuD/29pjCxHU7Lh5aPX3D/bhiXIJPbP1YpOHDPwHp2qpUvF4E3bAoAABDwmJgKf9WkSRORXrZsmZ5N/vzzz1F/++6778Tnu3fvfvNvkyZNcr+TSpUqybdPR48e9TDjJvO0gzI2Nja3P9l8Hho1aiTS586d0zM39ddff3UzxJKVlTV69Gix2LFjx88//1x+eh/0k5/IqGla7969dW4YHBws98SlpKSsWLHCzJxpmqZpP/zww7p168Rinz59ihYtavpR3Pj888/FEe/cufPyyy/n2e1boUKFbt26icVdu3ZNnDjRwKH37dv37bffGtjQsNKlSzds2FAsrly50v368pMdq1Wr9uCDD3p6RPtjsomBVHEVKlSQi/PixYt//vlnj/YQHx8vOtY1TatRo8ZDDz3kss4zzzwjv8/w/fffP3jwoIHc7ty5c8KECWIxOjrarP+48rQIy88s/PPPP3fs2OHpEbdu3SovyqOAylLzLMlPbfzll1/E3EWdli9fLn+L6OholxUU+a0VyYY3nn766YoVK4rFMWPG5BkHTp48+a9//cuZ/s9//tO5c+fExMStW7fKcaBmzZqdOnXKcXOrrw01GWuQ2FARwCO21ZsBEFu8FHhNFMXR8syRyz8b6Xy+uJpHyZG/hxr1ryj7A4WeHhh//93dUP+SQD6UZ5AP4CJpgLGwacMNJrdmMoJtnnw+IOIRflDo578DZ2YxUE+pVsTatWsXERHhTC9atMjhcFy6dEm8QOyJJ55QOV75hOJD8JpPuxT0UK0IAKawLjKocHvo1zWFue1wWj60fNRUvHhxedH9PNKLFy/Ki1FRUTmupubAPQPrLlQrX9kF2LApAABAwGNiKvxVq1atRPrrr79OSEjIc5Phw4d/8LeTJ0+Kz+Pj4z/629ixY/O8H5YfxWTRoyj1k+dH6ekE3L17d25/svk8REdHi/4aTdOmTp2a5yaffvqpm79u3LjxyJEjznRYWNhnn33maZbglJWVJb94tmHDhtWrV9e/uUtH+bx580zLmaZpmrZmzZqXXnpJLEZERLz77rvmHiJPFStWHDt2rFhcv3794sWL89xq9OjRhQoVEotjxozZsGGDR8e9fv16t27dMjIyPNrKex06dBDp77//3v3Kc+bMEWn56WX62R+TTQyk6hs6dKi82L9/f4+eUPjKK68kJSWJxRdffDH7OqGhoXIBSUtL69at24ULFzzK56lTp3r27CmPf3/44YdmPWvA0yLcsmVLucJ64403PH186YwZM0S6evXqHgVVX1HzLMXExIj0tWvXvvrqK/37v3v37vjx48VipUqVGjRo4LKOIr+1ItnwRoECBeQnhqalpXXv3t1lpMpF1apVR4wYIRZXr17dpEmTvn37yt997NixucUBq68NNRlrkNhQEcAjttWbARBbvBR4TRT10fLMzuVuzqIXj9hzlBz5e6hR/4qyOVDo7IHx99/dDfUvCeRDeQb5AC6SBhgLm/bcYHJrJhBs3VNhQMQj/KDwiP8OnJnCQD2lWhErWLBgly5dnOnLly9v3bp1yZIl4v/Fe/bsaWCfAUzxIXgnH3Yp6KFaEQC8Z2lkUOH20H9rCiva4bR8aPko6J577pEX5f+nzW7t2rUiXbRoUZcXrQtqDtwzsO5CtfKVXeANmwIAAAQ2JqbCX7Vv375SpUrOdHJy8rBhw9yvv3PnzuXLl4tF+R64SpUqIp2UlJRnv8+WLVtEWn50kE+Eh4eLtPveAU3Tpk+ffubMmdz+avN5KFSoUJ8+fcTikiVLVq9e7Wb9VatWuV9hyZIlIt2hQwf568Aj69evv3r1qliUfyY9GjduLJ/8X375Rc+8cT3S0tImTpzYtWtX+eGskydPLleunCn798hrr70mP2Dy/PnzeW5Ss2ZN+SFh6enpHTt21N9pcu7cuZYtW3rUw2WWf/7znwUKFHCmDxw48NNPP+W25tatW8UzI4OCgoz1qdkfk00MpOqrXbv2wIEDxeLly5dbtWrlfraY8Mknn8hXbLly5V599dUc1+zXr5/8DLzTp0+3aNHixIkTOjN56NChFi1ayD2eMTExbdq00bm5Hh4V4cKFCz///PNicfv27QMHDtT/WMc5c+bI9ZenQdWHFDxL7du3l5+7+fbbb+ucKO5wOF566SW58P7P//xP9tUU+a0VyYaXnnvuOfnQp06datGihfyG6uxGjRo1Z84cMSJ7+PDhs2fPir++9NJL8oOEXVh9bSjLQIPEnooAHrGn3gyM2OKlAGuiqI+WZ3YhISHy4s2bN/33KDkKgFCj/hVlT6DwqAcmAH53N9S/JJDf5BnkA7tIGmAgbNpzg8mtmYxgmyOlBkQ8wg8K/fx34MwsBuop1YqY/LK+hQsXip8vLCzM2ONrA5iyQ/AyH3Yp6KRaEQC8ZGlkUOT20O9qCuva4bR8aPkoKCIiolq1amJx8eLF165dy3HN+Ph4+bXMzZs3Dw7O+T/PlR24Z2DdhWrlK7sAGzYFAAAIbExMherS0tJy/DwkJGTw4MFicebMmePGjcttJydOnOjcubN4SFWzZs0aNWok/lq9enV5LtOQIUNSUlJy29Vvv/22dOlSsdiuXTsDmdc0LTo6Okpi+M2rcu/A7Nmz3aw5ffr0N954Q/7EpcPR/vMwcOBAuZPimWee2bFjR45rHjhw4Nlnn3VzCE3T5NlrjRs3vu459/vPP+bOnSvSwcHBzzzzjKd7kDdJS0uTLxUD7ty5s2/fvjFjxtSsWfOdd965c+eO+FOPHj3khxTaKSQkZObMmS6Dc3l644035Lc93717t1evXs8995z7R45lZmZ+8803Dz/88OHDh52fNGzY0ECeDatUqVLfvn3F4htvvJFjeUlMTBw4cKCItN27d69Vq1aOO3QfAO2PRSYGUv0H9aH//Oc/9erVE4tnz56tV6/eN99842aTO3fuDBgw4PXXX5c//OCDD8LCwnLb5Msvv5SHwc6fP1+/fv0PPvhAHr/JLjk5efjw4Q0bNrxy5Yr4MDo6Wn4Tryk8LcLvvvtuiRIlxOKsWbN69Ohx6dIl91s5HI5Zs2bJfeVlypRxOY0qU/AsFS1adMyYMWLx1q1bbdq0+fjjj90/tHvXrl2tWrX64YcfxCfly5d3ebalnd9CD0Wy4aUvvvhCfg31uXPn6tWrN378eDeBsU+fPkuWLMk+iFWjRo2PP/7YzbFsuDbUZKxBYk9FAI/YU28GRmzxUoA1UdRHy9NF6dKl5cXTp0/771FyEwChRvErytJAYbgHJgB+dzcUvySQ3+gJ8oFdJD1lIGzadoPJrZmMYCuoOSDiKX5Q6OenA2dmMda8V6qItW3bNjIy0pmeM2eOeJjsE088UbRoUW/2HHhUG4LPkW+7FHRSqggAXrI6Mqhwe+gvNYU97XBaPrR8FNSpUyeRTk5OHj16dPZ17t69+/LLL8uj/G6eKK3swD0D69kpVb6yC7xhUwAAgEDmAJQk3s6nadqpU6dyXCc9Pd2lq6V9+/bbt2+X10lJSZk2bZrcgR4eHn7gwAGXXbm8cLVOnTorV65MS0uT14mLixszZozcj3DfffelpKQYy3zlypXlIyYlJeW4Wu3atcU6ly5dyr7C+++/L+9n2LBhycnJLuscOHBA7kQQ3nzzTZ+fB3l2saZpBQsWHD16dFxcnFjh1q1bU6dOzfHOfOLEiWK1O3fuyIcz4P9j786DpKgOP4D3LLuycmhAkUOpVfCERdGKeCFqeVGKBhQqnkGNWlaEJBW8i6TKGCNeFY+kEpPSxELLA7FKXE/wVlQSEVAUzwioAVxQXJRxBeb3x6Qm89uLt7MzPbOzn89fvTNvXr+e6X79unu/3ZWVlS22MF9ee+217NkNHDhw13Z6+eWXsyvMvsVUjx492ltbtq+//jr7m9x+++0zNR999NE5LOzixYuzF7bFSg4++OBMgV69erXYsJqamuzGNDFx4sTvv/++7ZbMmzcv+yOLFi1qXuYvf/lLpsDo0aPbtaS/+tWvmjfsnHPOaeMj69evHz16dJOPVFdXT5o0aebMmStXrty0aVO6ZDKZXLhw4TXXXLPXXntlF77wwgsbGhoyK/z555/frjbn5sMPP8ze6vfbb78PPvggu8DHH3+cHfivrq5+++23W6ttqx1gzH1RfjvSwJm2S2ZNnjJlSgerSnvvvfeynxObtu+++15//fXLli377rvv0sXWr1//xhtvTJs2rcl16CiKzjvvvK3O5d///nd26Ddt4MCBU6dOfe6559auXZspWV9fP3fu3Isuuij7volpu+6663/+85825hLbJvzEE09ss8022SW7d+9+wQUXPPTQQ6tWrdqyZUumZDKZXLx48S233HLAAQc0qfzee+9trTEF6tXL7FtKpVKbNm066qijmnykf//+11133UsvvfTZZ59l5rJu3brHH3984sSJTQpXVVU99dRTbcwihqUI0alXuYzly5fvs88+TVo1aNCgX/ziFy+88MK6devSxbZs2bJ69epnnnlm8uTJPXr0iJo599xzN2/e3PY3FsO6UR7baVqhdwTxrGBblccd6Pjx4zNLNHbs2A7W1qJ49puF7ltCht+tOeecczIfPPjgg8M/2N75ltkQpYPGjh2bmcVNN91UiFmU08gzlUpl3xt75MiROXwhmWeDR1F0ySWXFHEuheurC93VlE2fHFtHEc8ZmBIZRbemI3uZVIydTAflvJj19fXZTb3//vtzmPuuWWd7rrjiihbLlMgoMbsZEydOzLmeJgIHJPF08vFvkh3cykLEOb6K4QAzraAjpc5ySSKjiJ1tDAcj8eyOS6SbTYvtBy1Qr95BdsrtEtuFs3I6uRfPJnbTTTdlCrdx8DV58uTm7b/vvvtaLJz9YMAoiurr61ssViKraB4PP2O7BB/PaLNFMQwIM+xlcvuqu9pepkBnkPI4zI6nZyjo4WER9xQlNQ5vFyMfI5/mitttrly5MnvvH0XRxIkTv/jii0yBFStWHHHEEdkFdt5558wpixYV+rxKmV1Yb5HLphlxXjYFACBngqmUqAEDBmQOJPbYY4/p06fPmDFj2rRpTYJJy5Yt22GHHZoceNTU1Bx77LGnnHLKAQcc0OSwsKKioq6urvns1q1b1/yQqbKycq+99jrppJPGjh27zz77NDlVl0gkHn300Zwbv2uegqlr167N3IsrrX///mecccb06dOvvvrqiy66KLuGqqqq7P863WabbS6//PL7778/E5qK/3toaGho/kzFqqqqkSNHjh07dtSoUdmR1B49emSficgOpi5ZsiTqmJiDqTmYN29edoXZp6U66KuvvspUO3v27Oy37rrrrtyWd9iwYZlKKioqmp99yD7/216VlZWXXnppyMnfQgdTN2zYUFNT06R5Wz338c0337TxYM+Kioqddtop+76V2S699NJ0JQceeGD6lXiCqalU6r777mvyK4wfP3769OlXXnnlySef3CQZ3vaas9UOMOa+KL8daeBM2yXvwdRUKvX6668PHDiwxdUskUjsuOOObVx9Of7449s+y5xRX1/fxsbevXv3gQMHNvkps40YMaJJBLq5ODfh2bNnt3Yrvm7duu2444677LJLnz59mj/sMe13v/tdG40pUK9eZt9S2tdff93GXWCrq6sHDRrU2h1Ju3Xr9sADD2x1FjEsRYjOu8plW7t27aGHHtraZ6urqwcOHFhVVbXVuYwbN26rF9IKvW6UzXaaVtAdQWwrWNs6VzA1Fct+M1XgvqVTBFNTZTdE6YgYgqmpMhp5pvLx/5277757pob+/ftv3LixWHMpaF9d0K6mbPrk2DqKeM7ApEpmFN2ijv+HdDydTAd1rv9O7qCOjBI7ezA1pJNPxb5JlngwNYfxVQwnH9IKN1LqLJckshWrs405mNpe4bvjEulmM+L5QUWGmutEO+WMeC6cldnJvRg2scB4xmOPPdak8urq6oaGhhYL5xDP6KCOrKJ5PPyM7RJ8bKPN5uIMpqbsZXL6qrvaXiaeYGoOMsPs2HqGwh0eFnFPUVLj8PYy8jHyaaLo3eb111/fvKohQ4Ycd9xxI0eObNI5VFRUPPnkk1uts6DnVcrswnqLXDbNiPOyKQAAORNMpUS1+GC6KIqSy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width="600" alt />
-<p class="caption">Figure 9: test.fastq2_LEADING_0</p>
+<img 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width="600" alt />
+<p class="caption">Figure 9: test.fastq2_LAGGING_0</p>
 </div>
 </center>
 <p><br /><br /></p>
 </center>
 <div class="figure">
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width="600" alt />
-<p class="caption">Figure 10: test.fastq2_LAGGING_16</p>
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4VQJlX0/daFUBYjEpk8JDJ5SGQAnGgT5OFYJgkdMKlchSU1iELalSr6fssoTcIYXZSHUXGpOJsDvZDI5CGRyUMok8pVWEKZKIQyqaLvt4SyxJDI5CGRSUUis1NKMOJgAEBBK1euPO2008IvMzMzFy9e3K9fP0kft2/fvrPOOuu7774L/+bzzz93PdjdGF988UX//v3DL7Ozszds2NCiRYsY3/7hhx9edNFF4ZePPfbY7bffHmX5a6+91plw+vbtu2rVqjg3WQ8zZ878/e9/H3558sknr1q1KvLON2Fr167t3bt3dXW185fvvPNOXl5ejJ/4pz/96bHHHgu/fOaZZ26++eY4t1obzhGBQCCQn5+fm5vr/E1FRcWjjz46derUsrIy13v79+9/3333nXfeedK3UkNjxox59dVXwy8nT558//33R1n+448/Pv/888Mv+/fvv3z58rg+cfz48U899VT45fTp08ePHx/XGjRS534btnXrVueNhRo2bLhx48bIuwdFd/HFF7/55pvhlx988MGFF14Y1xp08eSTT06YMKGiosKvDTA4UMyaNeu6664Lv2zbtu369etd989zmThx4rRp05y/6d69+/fffx/jJ1511VVz5swJv3zttdcib+Fphptuuun5558Pv3z44YfvuuuuGN87duzYl156KfwyIyNj48aN7dq1i/KWoqKinJwc529M3W8ffPDBPXv2+LgBTzzxhI+fLhWJTB4SmTyEMqkIZZIQyqQilMlAIpOHRCYPiUweQpk81K08tAnycCyThA6YVKQGSUi7UjFKIwmji/IwKi4PZ3MkIZHJQyKTh0QmD6FMKkKZJIQyqQhlMpDI5CGRyUMisxYTUwE93HbbbU8++WT4ZVxjEIn59ttvnY9lv+GGG5yDICa55ZZbnnnmmfDLZ5999qabboprDf379//iiy9CP+fm5ubn50dZuLy8fMCAAc4uxbffflvjzWB0d8kll7z++uvhl7Ec6V19r5ycnMLCQldiieLHH3903mZj5MiRb7/9djybrJMYByA2b978+9///tNPP438U79+/W6//faRI0e67sxkuW7dum3YsCH0c2pq6sGDB9PT06Ms//TTT996663hlzNmzLj++uvj+kTXCNGFF174wQcfxLUGjcQ+cPbKK69ceeWV4ZdXX321czA9Rq6Ec9NNNz377LPxrkQXq1evvuyyyzZu3Oj6/YABA0444YQEVviPf/wj/HPHjh0HDRoUZeEE/ju6uPrqq19++eXwyzfeeGP06NHR37Jnz56cnJyqqqrwb6ZNm3b33XfH+Ilr167t1atX+KXBHbC+ffuuXr069HP9+vWLi4ubN28e43sPHz7cq1evH3/8Mfybq666yrnTRrLnBNtJJ520efNmHzfA1IoNkMhkIpHJQyiTilAmCaFMKkKZJCQySUhk8pDI5CGUyUPdykObIA/HMnnogMlDapCEtCsVozSSMLooD6Pi8nA2RxISmTwkMnlIZFIRyuQhlElCKJOKUCYDiUweEpk8JDJ7ef2IVgAJGTBgQPhrm5WVdeDAAQ8+dPDgweEPHThwoAef6AtniG3YsOHBgwfjXcPTTz/tbFfz8/OjL//ee+85l7/zzjsT3Xal9ejRI1zG9PT06urqOt/yr3/9y1kzl19+ebwfeuyxx4bf3qtXr4Q2XA+uo3n0ve7VV1+t7VZYbdu2nTx58k8//eTZlivOObzbvXv3Ope/5557nPW5YcOGBD7UGcJ79uyZwBp0Eft++9e//tW55BtvvJHAx1VVVTn/oWeccUYS266BkpKSyPGvrKysF154IYG1OVeSl5cnfGt14Yys2dnZsRzLgsFgnz59nBW4ZMmSuD60VatW4feeeuqpiWy3DpwHpgSKuXDhQmclp6SkrF69Osryu3btcn07kth2pTnHB33hdwVIRCKTh0QmD6FMKlcDSCgThVAmVez7LaEsXiQyGUhk8pDI5CGUyUPdykObIA/HMqnogEniqlJSgyikXali32+DjNLEg9FFeRgVl4ezOZKQyOQhkclDIpONUCaJq0oJZaIQyqSKfb8NEspiRiKTh0QmD4nMWrU+zRmAUnbu3Bn+OTc3t3Hjxh58qPMx5QUFBR58oi9++umn8M/9+vVr1KhRvGsYOHCg8+WKFSuiLz906FDnvcfWr18f7ydqYc+ePeGfu3TpEss9V7p16+Z82blz53g/tGvXruGfd+/eHe/bTXXJJZds2LBhypQpGRkZrj8VFhZOnjz52GOPHTVq1Ntvv11WVubLFqrj8OHD4Z9dO2SN9u3b53zZtm3bBD7UeaO4yCFgOxUVFTlf9u7dO4GV1KtXzznK7FqneTIyMmbMmPHee+9lZ2eHf3n48OFx48YNHz68uLjYx23T1y+//BL+uV+/fjHeP8x1O6t4z9I591vnwdQwe/fuDf98/PHHx/v2Cy64YMSIEeGXwWDw9ttvF7NlmjvmmGP83gRjkcjkIZHJQyhTB6EsdoQyRRDK4kUik4FEJg+JTB5CmTzUrTy0CfJwLJOKDpjvSA1xIe2qg1Ga2DG6KA+j4vJwNkcSEpk8JDJ5SGSyEcp8RyiLC6FMHYSyGJHI5CGRyUMisxYTUwE9FBYWhn923o5CKudgh/MYbBhn3dZ2F5bo2rVr53z5888/R1++Xr16Xbp0Cb/ctm1bAh+qPufgToxjNK7FWrRoEe+HtmzZMvyzwX3iBKSnp993330//PDDlVdeWb9+fddfKysr33777VGjRrVq1eryyy9fsGBBeXm5L9vpu/bt24d/LikpqXN558haIBBITU1N4EOdqebgwYMJrME8rjGF1q1bJ7YeZ5tgyeDO8OHDv/vuuwsuuMD5y/nz5/fo0cN11yXEwnkSyHljy+hcHYNmzZrF9aHOhsXgExWVlZXhnzMzMxNYwxNPPJGWlhZ+uWzZsrffflvAlmnuq6++WrBgwTXXXJNYrSIKEpk8JDJ5CGVKIZTFiFCmCEJZYkhkYpHI5CGRyUMok4e6lYc2QR6OZR6gA+YjUkNcSLtKYZQmRowuysOouDyczZGERCYPiUweEpk3CGU+IpTFhVCmFEJZLEhk8pDI5CGRWSuRwyQA7zVp0iR8DyHXjVjkcd4hpkmTJt58qPeqq6vDPycWHlx3bYklmzl7JNu3b0/gQ9WXkZFx4MCB0M/O/nEUrsWOHDkS74c6w3ZWVla8bzde+/btX3755XvuuWfq1Kmvvfaac+cPOXTo0Ny5c+fOnZuZmXnWWWedd9555513Xm5uri9b64tjjz12y5YtoZ/DP0TRpk0b58vi4uIEetLOTOK8KY7NmjZt6nxZr16C91IJBoMiNkczOTk5H3744TPPPHPnnXeGW8Xdu3fn5eVdd911TzzxBM1j7JztpPOEUHTOAZpAIOA8CRQL5+3Njh49Gtd7NZKTkxMeYUnsPlXHH3/8hAkTHnjggfBvJkyYcOGFF8Zb4YZJS0u76KKLLrroounTp0+fPv2hhx6KvH1gz549rTq4i0Iik4dEJg+hTEGEsjoRyhRBKEsYiUwgEpk8JDJ5CGXyULfy0CbIw7HMG3TA/EJqiAtpV0GM0tSJ0UV5GBWXh7M5kpDI5CGRyUMi8wyhzC+EsrgQyhREKIuORCYPiUweEpm1mJgK6KFDhw7hZvqHH37w5kOdH9ShQwdvPtR7OTk5P/74Y+jnxG6TEP7XhMQyHrFjx47wz5GdaTO0bNky3CeO8aHzrsXqvINIJOedNlzjRAjr0qXL3LlzJ02a9MADD7z++utVVVWRy5SUlHz44YcffvhhIBBo27Zt//79+/bt26dPn969ezdu3NjzTfZOp06dlixZEvp548aN69at6969e5TlXXcY+uabb+IdgKisrFy7dm34pes+OtZy3qIskOjITiAQCDfvgYjRIrOlpKTccsstgwYNGjNmzLfffhv+/Ysvvvjpp5/OmTPnjDPO8HHzNNK8efPwkWXnzp0xvss17hAvZyA3eFDSeYJt48aNia3k7rvvnjNnTnikZsuWLVOnTp02bZqQLdRd48aN77vvvuHDh5977rmuYcff/e53EydO9GvD9EUik4dEJg+hTFmEsigIZYoglCWDRCYKiUweEpkHCGXyULfC0SbIw7HMM3TAfEFqiAtpV1mM0kTB6KI8jIrLw9kc2UhkwpHI5CGReYlQ5gtCWVwIZcoilNWGRCYPiUweEpm1Erw9BgCPderUKfzzjh07Fi1aJPsTjxw58q9//Sv80uBm2jkEsHLlyvLy8njXsGbNmtpWWJv8/Pzwz61atYr3E7Xg3Gd27dq1Z8+eOt/irJZAIPD555/H9YlHjhz5+uuvwy9bt24d19tt07Vr17lz527ZsuWuu+5q3rx5lCULCwvnzZs3YcKEs88+u2nTpl27dvVsI72Xl5fnfPn4449HX37gwIHOe4+9//778X7iokWLnIP1iQ0Pmcc1HLlp06bE1mPJwFltcnNzV61adfvttzvvyLhly5azzjpr4sSJFRUVPm6bLlq0aBH+ed26dTGOCDRr1izHId4PdZ5tMni/ddbMtm3b4j3oh6Snp0+fPt35m7/97W+rV69OduMM0qtXL2eXHskgkclDIpOHUKY4QlmNCGWKIJQlj0SWPBKZPCQyzxDK5KFuBaJNkIdjmcfogHmM1BAX0q7iGKWpEaOL8jAqLg9nc7xBIhOIRCYPicx7hDKPEcriQihTHKEsEolMHhKZPCQyazExFdDD//3f/zlfTpw40fm0dBmmTZvmvJ3D+eefL/XjfNSvX7/wzwcPHkwgP7z77rvOl64bEUX6+OOP9+/fH37pPAab5Mwzz3S+fPjhh6MvX1pa+tRTTzl/s3r16oKCgtg/cf78+c7vxWmnnRb7e63VsWPHhx9+eOfOnTNmzDj55JPrXD4YDHp2CxNfDBkypG3btuGXs2fPnjdvXpTlGzRo4ByzmDt3rvOuNnWqrq6+9957nb8ZNmxY7G83WI8ePZzx4K233kpgJV9//XX4llGBQOD4448XsGW6adiw4WOPPfbxxx87b7pWVVU1bdq0U089dd26dT5umxa6dOkS/nnXrl2ffPJJLO8aNWrUzw7169eP/RMLCwstGfDt37+/82WdA761ycvLGzp0aPhlZWXlpZdeeujQoaQ2ziyDBw8+55xz/N4KE5DI5CGRyUMo0wKhzIVQpghCmRAksiSRyOQhkXmJUCYPdSsKbYI8HMu8RwfMS6SGuJB2tcAojQuji/IwKi4PZ3M8QyIThUQmD4nMF4QyLxHK4kIo0wKhzIlEJg+JTB4Smb2CAHRQUlKSlZXl/PIOHTr06NGjkj7OdQ+t9PT0/fv3S/os3y1dutRZ2BNPPLGsrCz2t2/evPmYY44Jvz0lJeXnn3+OsnxZWdlJJ53k/MSHHnoo6UKoaNmyZc5iNmjQYP369VGWnzRpUuRB6sYbb4zx4yorK3v06OF876JFi0SUQ1GuisrPzxey2nXr1t1zzz113pxJyGcpyzUikJ6e/tZbb0VZft26dQ0bNgwvf/7551dWVsb4WRMnTnR+VkZGxuHDh0UUQlFx7bfTpk0LL9msWbPi4uJ4P27IkCHOj5s3b14S2669X375ZdSoUa5/QVpa2vTp06urqyOXdy6Wl5fn/QYr4tlnn3VWxbnnnltjdQl03333OT9x0qRJUj/OR1u3bnXtkDNnzkxsVdu2bcvIyHCu6uyzzz5y5IhzmV27drk+TkQhtPHSSy85y/6Xv/zF7y3SEolMHhKZPIQyqVwVRSgTiFAmT1z7LaFMIBJZYkhk8pDIPEYok4e6FYI2QR6OZT6iA5YwV6WRGgQi7coT134bO0ZpGF2Uh1FxeTib4yUSmRAkMnlIZP4ilCXMVWmEMoEIZfLEtd/GzvJQRiKTh0QmD4nMWsa2xYB5JkyY4OoudO3adenSpWI/ZevWrcOHD3d90DXXXCP2U5RSWVnpeoT6b3/726qqqljeW1JScuqppzrf27dv3yjLHzhwwHUriIC4Lrhqqquru3bt6ixpx44dlyxZErlkRUXFlClTUlNTAxHq1au3cOHCWD7O9QVp2rRpaWmp4CKpROpeVF1dvXz58gkTJnTr1i3ynxIwN8iFHDp06IQTTnAV+brrrisqKqrtLX/5y1+cC48dO7a8vDz6p1RVVU2ZMsX1KWPHjhVdGrW4ynvBBRf8+c9/fvHFF5cuXbpz507XsOO+fftat24dXnj06NFxfdZHH33k/KyGDRsePHhQaGm0NHv2bFfqCwQC55xzTkFBgWtJ5wI2D/hG3lNN6qDAli1bmjZt6vw4UzsJIX379nV9T//5z38mtqqnn37a9Z8aNmxYRUVFeAGrTrBFKioqcpads8IJI5FJQiKTh1AmldQdiVBGKJPEVV5CmcdIZPEikUlFIvMSoUwe6lYU2gRJOJb5jg5YAlzVRWoQiLQrj6u8jNKIwuiiPIyKS8XZHM+QyEQhkUlCIlMBoSwBruoilAlEKJPHVV5CmRAkMnlIZFKRyOxkbFsMmKekpKTGJ3cPGDBg9uzZSeaB8vLy+fPnX3zxxc77u4R06NDhl19+EVUKNT333HOuUg8bNqzOUu/YsWPAgAGuN7744os1LlxdXb1kyZITTzzRtfzw4cMlFEgVs2bNcpU3JSXlhhtuWL58+d69e48ePbpz587XX3/9lFNOcS6Tnp6emZkZftm4ceMPP/wwyqdUV1dH3ujlvvvu86yYvnCVV14ndfPmzU888cSQIUMaNWoU/jhJn6WOL7/8MjKkpaWljRs3btWqVZHxo7y8fMSIEc6FTz/99FWrVtW2/lWrVp199tmu9bdp08b4xjYQVXp6es+ePUeOHDlhwoQZM2Z88sknjzzyiHOBKVOmxPhBr732WlpamvO9I0aMkFo0jWzevLlfv36uym/WrNmrr77qXMz5V8sHfF23BgwEAn/4wx9kDLsUFBS47jrWs2dP4Z+ilDfeeCOyKbj00kvXrFmTwNoiR3BOP/308PHRqhNsNXLePpCzwgkjkclDIpOHUCaPq7yEMrEIZZIEoiKUeYBEFi8SmTwkMo8RyuShboWgTZCHY5nv6IDFK7I1cCI1JIm0K4mryIzSCMToojyMisvD2RwvkciEIJHJQyJTAaEsXpENghOhLEmEMklcRSaUiUIik4dEJg+JzE4mt8WAeZYuXepKAmGpqam9e/e+6aabXnzxxUWLFq1fvz5Kw11aWrpp06YlS5bMmTPnjjvu6N+/f3p6em2r/eKLL7wsoy8qKipcD0kPBAItW7Z88MEHCwsLI5ffunXr3Xff3aRJE9dbunbtWllZ6Vq4rKzszjvv7NixY2T1pqWlfffdd54U0R+VlZX9+/evcdeK4oknnnjyySedv6lfv/611167efNm1/pDnbYzzjjDtYZGjRoZ37dwFdmDu6dUVlauWrXqkUceueiii2R/lgqefvrplJSUGnfRFi1a/Pa3v3300Uffe++9devWlZSUBIPBysrKa6+91rVk//79p02b9sEHH6xatWrlypXvv//+5MmTI8faQhYsWOB3oaWLoyGoRZ1jZwUFBXfccYfrf5eammr2HYbiVVFRcf/999evX99VvZdeeunevXtDyzh/b/mA74oVKyJ3xZycnBtuuOGDDz748ccfDx48GHn0j8vRo0dnzZqVnZ3t+pTHH39cVCmUNXr06Bq/7CeddNL48eNnzJixcOHCGM+37d+/P3Icp0GDBrfccssnn3yybds2159kF001eXl54bJzVjgZJDJJSGTyEMrkcRWZUCYcoUyGOBqCWhDKkkciiwuJTCoSmZcIZfJQt6LQJkjCsUwFdMDiUmNTEBdSQ3SkXRlcRWaURiBGF+VhVFwqzuZ4hkQmColMEhKZIghlcamxNYgLoSw6QpkMriITykQhkclDIpOKRGYhw3MFYJ7FixdnZGRE6U841a9fPysrKzs7u3379u3bt2/ZsmWjRo0aNGgQ49ubNm36wQcf+F1ij3zzzTfOG4Q4de/efeTIkePGjbv66quHDRt23HHH1XZIW7JkSeSa9+zZU1sN13aTDJNs3769RYsWMe5ygUBg8ODBVVVVVVVVNYa03NzcK6644o477rj11ltHjx6dk5NT40r++c9/+l1u6VxFtmRQwGNvvvlmjO1tvXr1Gjdu3KZNm9h3daeGDRvOmTPH7+J6IbH6ceratWttK//qq69GjBgROYgZCARuu+02L4upixUrVkTel6h9+/aLFi0KMuD7/7rzzjuj75n9+/ePd50FBQVLly6dNWvWVVdd1bp168h1nnbaaRUVFTKKo5SioqLajubO3TLGtW3durV9+/Y1riTyFllSy6Wgu+66K1x2zgoniUQmCYlMHkKZJK4iE8pkIJQJl1j9OBHKRCGRxY5EJg+JzEuEMnmoW1FoE+ThWKYIOmAxir67xoLUUCfSrnCugjNKIxaji/IwKi4VZ3O8QSIThUQmD4lMHYSyGEXfY2NBKKsToUw4V8EJZQKRyOQhkUlFIrON+bkCMM/KlSt/9atfxdjUJqxHjx6bNm3yu6yeev/992tMXDGaMWNGjautsXtRr169J5980uMC+iU/P79du3ax1OGvf/3rPXv2hN71/fff13Zbi+huuOEGf8vrDVepCXKSrF69OvKmOGK1bNly+fLlfhfUI7fffvvw4cNzc3MT+3YHog6c3XvvvTW+pVevXgcOHPCymBo5ePDgVVdd5aqxlJSU8ePHO39j+YBvMBisqqpy3uo1UgInKgYOHBhlhU2aNNm6dauEoqho69atPXr0iFIbsZ9gCwaDP/zwQ23n2FzklUhN//jHP9L+56GHHvJ7c7RHIpOERCYPoUwGV6kJZZIQysQilCmFRBYjEplUJDLPEMrkoW4Fok2QhGOZOuiAxYLU4A3SrliusjNKIxyji/IwKi4VZ3M8QCITiEQmCYlMKYSyWBDKvEEoE8tVdkKZWCQyeUhkUpHIrGJ+rgCMVFVV9eKLL9Z5o6zEHH/88TNnzjx69KjfpfTB4sWLs7Oz462xBg0aPPPMM7WtM7J70aFDhwULFnhZLt/t2LFjxIgR0atx4MCBrnC7bNmyyKfeR/eHP/yhsrLSr2J6yVVwgpw8FRUVs2bNqu2GN8lo2LDhn/70p7179/pdRB9UV1f/9NNPy5Ytmz179sSJEy+55JK+ffs2b968zkqLd+DsN7/5zS+//OJl0XQ0b968Zs2aRal2ywd8Q6qqqiZNmlSvXr0aq0jsiYqWLVsuXrxYRimUdfDgweHDh9dWIXGdYAsGg7t37x48eHCUXTpEUllgDxKZJCQyeQhlwrkKTiiTh1AmA6FMHSSyWJDIpCKRAXCiTZCEY5lS6IDFiNQgG2lXIFcNMEojA6OL8jAqLhVnc6AXEpkkJDLVEMpiRCiTjVAmkKsGCGXCkcjkIZFJRSKzhxW5AjDV4cOH58yZk5eXl/CtcZzS09MvvPDCl19+uaKiwu+S+Wn79u1DhgyJvd5OOumkL774IsoKnd2LDh06TJ069fDhw54VRymffPLJmDFjGjdu7KrDXr16zZ49u8aewdq1a2PsjjRu3PjZZ5/1vlB+cRWfICdbeXn5Sy+9NHToUCHtbU5Ozk033bR9+3a/i6WcvXv3/ve//33ttdcefPDBsWPHnnnmme3atUtJSQlXXVwDZ6NHj7Zz1CwBBQUFgwYNqm2PZcA3bMWKFcOGDXPukyECT1QMGjSosLBQxsarb+HChaeddlpkncR7gi0YDFZVVc2YMSP6veJkFAEWIpHJQCKTilAmkKv4hDLZCGXeIJT5gkQWIxKZVCQyAE60CZJwLFMHHbBkkBrEIu0K4aoHRmnkYXRREkbFZeNsDvRCIpOERKYUQlkyCGViEcqEcNUDoUwSEpkkJDLZSGQ2SAlGHAwAaKekpGThwoVffvnlunXr1q1bF+rU1vmuevXqdezYsXPnzt27dx88ePDAgQOFNPdm+PLLLx966KGPP/74yJEjtS3Ts2fPP/3pT5dddln0x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width="600" alt />
+<p class="caption">Figure 10: test.fastq2_LEADING_0</p>
 </div>
 </center>
 <p><br /><br /></p>
 </center>
 <div class="figure">
-<img 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QEwok2Qw7lMAh0wUabCkhpsRNqVU+VxyyiNLRhdlMOouCiu5sBbSGRySGRCCGWiTIUllNmIUCanyuOWUJY4EpkcEpkoEpmGfN4/A/zkvffei2xDr7766h9++MGuTeTn50+fPj01NdW0lUWLFtm1CTW98MILpiL36tVr+/bt0T+1cePGjh07hj+SkpLy9ddfV7nkyZMn582b165dO9NWhg0bJlAahUR2LEaMGHHgwAHTYmvXru3QoUOVXZBAIDB27NgoQS7k6NGjv/zlL42f6tu3r1ixlGCqpfAARElJyX333WeKGYFAoFOnTkuWLHF3nz3h6NGj9evXN1ZdkyZNokesUaNGGZevV69edaPDJlu2bGnevLnxs/3797epHIqq7rit0uTJk03L33777TW2BiHfffdd48aNjZ+dOHGiTYVQEQO+on7zm9+YytuqVau33nqrsrLSuFhhYeELL7xg7EQZm+ImTZpEP+CDweD69etN4xFXX321ZMlcdvToUdM4bO/evY8ePRr9U/PmzTMNK3Tu3PnUqVM1bk63C2wQQiKTQyKTQyiTY6olQpldCGWiqjtuq0Qos4hEJopEJoREBsCINkEU5zIJdMBEmQpLarALaVdUdcctozSJY3RRDqPicriaA28hkYkikQkhlIkyFZZQZhdCmajqjltCWYJIZHJIZHJIZHryef8M8JMzzzzT2HQ2atTo3//+t8SGduzYYfqh8E6dOklsSBGVlZXt27c3lve8884rKiqy8tl9+/a1aNEi/MGePXuWlZVVt/DRo0cj+4ivvvqqfUVRy969e01x4vHHH69u4YKCgvPPPz+yI5KVlVVcXGxlczt27EhPTzd+Nvpjn7zOVFGmAYh169b16NEjsj4vuuiizz77zK199oQFCxYYa6xu3bpbtmyJsnxJSYnpwHv77betb279+vWmkeIdO3YkXAh1RT9uTUwPYRo6dGiVTyarzvLly41PLEtLS7PYmHgRA75ycnJyTE8dGzNmzPHjx6tb/j//+c9pp50WWUWLFy+2srmVK1caN1e7du3IgSTfeP31141V1KhRo5ycHCsf/Ne//mWq3unTp9f4Kd0usEEIiUwIiUwOoUyUqaIIZXYhlImKftyaEMosIpHJIZHJIZEBMKJNkMO5TAgdMFGmwpIa7ELaFRX9uGWUJm6MLsphVFwUV3PgLSQyOSQyOYQyUabCEsrsQigTFf24JZTFh0Qmh0QmikSmp6RgxMkAgILWrVt33nnnhd+mp6evWLGib9++Qps7evToRRdd9P3334f/8sUXX5h+2N03vvzyy379+oXfNm3adOvWrU2aNLH48Y8++ujKK68Mv33qqafuueeeKMvffPPNxoTTp0+f9evXx7jL3jBv3rzf//734bdnn332+vXrI598E7Zp06ZevXpVVlYa//juu++OHDnS4hb/9Kc/PfXUU+G3c+bMueOOO2Lca88wjggEAoHs7OysrCzjX8rKyp588snp06eXlJSYPtuvX78pU6Zcdtll4nvpQWPHjn3ttdfCb6dOnfrwww9HWf6TTz4ZPHhw+G2/fv3WrFkT0xYnTJjw7LPPht/Onj17woQJMa3BQ2o8bsN2795tfLBQ3bp1t23bFvn0oOiuuuqqt956K/z2ww8/vOKKK2Jag1c888wzEydOLCsrc2sHfBwo5s+ff8stt4TftmrVasuWLabn55lMmjRpxowZxr9069bthx9+sLjFG264YeHCheG3r7/+euQjPP3h9ttvf/HFF8NvH3/88fvvv9/iZ8eNG/fKK6+E36alpW3btq1169ZRPpKXl5eZmWn8i1+P28cee+zQoUMu7sCsWbNc3LooEpkcEpkcQpkoQpkQQpkoQpkEEpkcEpkcEpkcQpkc6lYObYIczmVC6ICJIjUIIe2KYpRGCKOLchgVl8PVHCEkMjkkMjkkMjmEMlGEMiGEMlGEMgkkMjkkMjkkMm0xMRXwhrvvvvuZZ54Jv41pDCI+3333nfFn2W+99VbjIIif3HnnnXPmzAm/ff7552+//faY1tCvX78vv/wy9DorKys7OzvKwqWlpf379zd2Kb777rsqHwbjdVdfffUbb7wRfmvlTG/qe2VmZubm5poSSxQ7d+40PmZj1KhR77zzTiy77CUWByB27Njx+9///rPPPov8p759+95zzz2jRo0yPZlJc127dt26dWvodXJyckFBQWpqapTln3vuubvuuiv8du7cub/73e9i2qJphOiKK6748MMPY1qDh1gfOPvHP/5x/fXXh9/eeOONxsF0i0wJ5/bbb3/++edjXYlXbNiw4dprr922bZvp7/379z/jjDPiWOHf//738Ot27doNHDgwysJx/O94xY033vjqq6+G37755ptjxoyJ/pFDhw5lZmZWVFSE/zJjxowHHnjA4hY3bdrUs2fP8Fsfd8D69OmzYcOG0OvatWvn5+c3btzY4mcLCwt79uy5c+fO8F9uuOEG40EbSZ8LbGedddaOHTtc3AG/VmyARCaJRCaHUCaKUCaEUCaKUCaERCaERCaHRCaHUCaHupVDmyCHc5kcOmBySA1CSLuiGKURwuiiHEbF5XA1RwiJTA6JTA6JTBShTA6hTAihTBShTAKJTA6JTA6JTF9O/0QrgLj0798//LXNyMg4fvy4AxsdNGhQeKMDBgxwYIuuMIbYunXrFhQUxLqG5557ztiuZmdnR1/+/fffNy5/3333xbvvSuvevXu4jKmpqZWVlTV+5F//+pexZq677rpYN3r66aeHP96zZ8+4dtwbTGfz6Efda6+9Vt2jsFq1ajV16tSffvrJsT1XnHF4t1u3bjUu/+CDDxrrc+vWrXFs1BjCe/ToEccavML6cfuXv/zFuOSbb74Zx+YqKiqM/6EXXHBBAvvuAUVFRZHjXxkZGS+99FIcazOuZOTIkbbvrVcYI2vTpk2tnMuCwWDv3r2NFbhy5cqYNtq8efPwZ88999x49tsLjCemOIq5bNkyYyUnJSVt2LAhyvIHDhwwfTsS2HelGccHXeF2BQgikckhkckhlIkyNYCEMrsQykRZP24JZbEikUkgkckhkckhlMmhbuXQJsjhXCaKDpgQU5WSGuxC2hVl/bgNMkoTC0YX5TAqLoerOUJIZHJIZHJIZNIIZUJMVUooswuhTJT14zZIKLOMRCaHRCaHRKatan/NGYBS9u/fH36dlZVVv359BzZq/JnynJwcB7boip9++in8um/fvvXq1Yt1DQMGDDC+Xbt2bfTlhw4danz22JYtW2LdoiccOnQo/Lpz585WnrnStWtX49tOnTrFutEuXbqEXx88eDDWj/vV1VdfvXXr1mnTpqWlpZn+KTc3d+rUqaeffvro0aPfeeedkpISV/ZQHYWFheHXpgOySkePHjW+bdWqVRwbNT4oLnIIWE95eXnGt7169YpjJbVq1TKOMpvW6T9paWlz5859//33mzZtGv5jYWHh+PHjhw8fnp+f7+K+edfhw4fDr/v27Wvx+WGmx1nFepXOeNwaT6Y+c+TIkfDrDh06xPrxyy+/fMSIEeG3wWDwnnvusWfPPO60005zexd8i0Qmh0Qmh1CmDkKZdYQyRRDKYkUik0Aik0Mik0Mok0PdyqFNkMO5TBQdMNeRGmJC2lUHozTWMbooh1FxOVzNEUIik0Mik0Mik0Yocx2hLCaEMnUQyiwikckhkckhkWmLiamAN+Tm5oZfGx9HIco42GE8B/uMsW6rewpLdK1btza+/fnnn6MvX6tWrc6dO4ff7tmzJ46Nqs84uGNxjMa0WJMmTWLdaLNmzcKvfdwnjkNqauqUKVN+/PHH66+/vnbt2qZ/LS8vf+edd0aPHt28efPrrrtu6dKlpaWlruyn69q0aRN+XVRUVOPyxpG1QCCQnJwcx0aNqaagoCCONfiPaUyhRYsW8a3H2CZoMrgzfPjw77///vLLLzf+ccmSJd27dzc9dQlWGC8CGR9sGZ2pY9CoUaOYNmpsWHx8oaK8vDz8Oj09PY41zJo1KyUlJfx29erV77zzjg175nFff/310qVLb7rppvhqFVGQyOSQyOQQypRCKLOIUKYIQll8SGT2IpHJIZHJIZTJoW7l0CbI4VzmADpgLiI1xIS0qxRGaSxidFEOo+JyuJojhEQmh0Qmh0TmDEKZiwhlMSGUKYVQZgWJTA6JTA6JTFvxnCYBOK9BgwbhZwiZHsQix/iEmAYNGjizUedVVlaGX8cXHkxPbbGSzYw9kr1798axUfWlpaUdP3489NrYP47CtNjJkydj3agxbGdkZMT6cd9r06bNq6+++uCDD06fPv311183HvwhJ06cWLRo0aJFi9LT0y+66KLLLrvssssuy8rKcmVvXXH66afv2rUr9Dr8IoqWLVsa3+bn58fRkzZmEuNDcXTWsGFD49tateJ8lkowGLRjdzwmMzPzo48+mjNnzn333RduFQ8ePDhy5Mhbbrll1qxZNI/WGdtJ4ySREHQAACAASURBVAWh6IwDNIFAwHgRyArj481OnToV02c9JDMzMzzCEt9zqjp06DBx4sRHHnkk/JeJEydeccUVsVa4z6SkpFx55ZVXXnnl7NmzZ8+ePXPmzMjHB/bo0UOrk7tdSGRySGRyCGUKIpTViFCmCEJZ3EhkNiKRySGRySGUyaFu5dAmyOFc5gw6YG4hNcSEtKsgRmlqxOiiHEbF5XA1RwiJTA6JTA6JzDGEMrcQymJCKFMQoSw6EpkcEpkcEpm2mJgKeEPbtm3DzfSPP/7ozEaNG2rbtq0zG3VeZmbmzp07Q6/je0xC+L8mxMp4xL59+8KvIzvT/tCsWbNwn9jij86bFqvxCSKRjE/aMI0TIaxz586LFi2aPHnyI4888sYbb1RUVEQuU1RU9NFHH3300UeBQKBVq1b9+vXr06dP7969e/XqVb9+fcd32TkdO3ZcuXJl6PW2bds2b97crVu3KMubnjD07bffxjoAUV5evmnTpvBb03N0tGV8RFkg3pGdQCAQbt4DEaNF/paUlHTnnXcOHDhw7Nix3333XfjvL7/88meffbZw4cILLrjAxd3zkMaNG4fPLPv377f4KdO4Q6yMgdzHg5LGC2zbtm2LbyUPPPDAwoULwyM1u3btmj59+owZM2zZQ6+rX7/+lClThg8ffumll5qGHX/zm99MmjTJrR3zLhKZHBKZHEKZsghlURDKFEEoSwSJzC4kMjkkMgcQyuRQt7ajTZDDucwxdMBcQWqICWlXWYzSRMHoohxGxeVwNUcaicx2JDI5JDInEcpcQSiLCaFMWYSy6pDI5JDI5JDItBXn4zEAOKxjx47h1/v27Vu+fLn0Fk+ePPmvf/0r/NbHzbRxCGDdunWlpaWxrmHjxo3VrbA62dnZ4dfNmzePdYueYDxmDhw4cOjQoRo/YqyWQCDwxRdfxLTFkydPfvPNN+G3LVq0iOnjuunSpcuiRYt27dp1//33N27cOMqSubm5ixcvnjhx4sUXX9ywYcMuXbo4tpPOGzlypPHt008/HX35AQMGGJ899sEHH8S6xeXLlxsH6+MbHvIf03Dk9u3b41uPJgNn1cnKylq/fv0999xjfCLjrl27LrrookmTJpWVlbm4b17RpEmT8OvNmzdbHBFo1KhRpkGsGzVebfLxcWusmT179sR60g9JTU2dPXu28S9//etfN2zYkOjO+UjPnj2NXXokgkQmh0Qmh1CmOEJZlQhliiCUJY5EljgSmRwSmWMIZXKoWxvRJsjhXOYwOmAOIzXEhLSrOEZpqsToohxGxeVwNccZJDIbkcjkkMicRyhzGKEsJoQyxRHKIpHI5JDI5JDItMXEVMAb/u///s/4dtKkScZfS5cwY8YM4+McBg8eLLo5F/Xt2zf8uqCgII788N577xnfmh5EFOmTTz45duxY+K3xHOwnF154ofHt448/Hn354uLiZ5991viXDRs25OTkWN/ikiVLjN+L8847z/pntdWuXbvHH398//79c+fOPfvss2tcPhgMOvYIE1cMGTKkVatW4bcLFixYvHhxlOXr1KljHLNYtGiR8ak2NaqsrHzooYeMfxk2bJj1j/tY9+7djfHg7bffjmMl33zzTfiRUYFAoEOHDjbsmdfUrVv3qaee+uSTT4wPXauoqJgxY8a55567efNmF/fNEzp37hx+feDAgU8//dTKp0aPHv2zQe3ata1vMTc3V5MB3379+hnf1jjgW52RI0cOHTo0/La8vPyaa645ceJEQjvnL4MGDbrkkkvc3gs/IJHJIZHJIZR5AqHMhFCmCEKZLUhkCSKRySGROYlQJoe6tQttghzOZc6jA+YkUkNMSLuewCiNCaOLchgVl8PVHMeQyOxCIpNDInMFocxJhLKYEMo8gVBmRCKTQyKTQyLTVxCAFxQVFWVkZBi/vEOHDj116pTQ5kzP0EpNTT127JjQtly3atUqY2HPPPPMkpIS6x/fsWPHaaedFv54UlLSzz//HGX5kpKSs846y7jFmTNnJlwIFa1evdpYzDp16mzZsiXK8pMnT448Sd12220WN1deXt69e3fjZ5cvX25HORRlqqjs7GxbVrt58+YHH3ywxocz2bItZZlGBFJTU99+++0oy2/evLlu3brh5QcPHlxeXm5xW5MmTTJuKy0trbCw0I5CKCqm43bGjBnhJRs1apSfnx/r5oYMGWLc3OLFixPYd887fPjw6NGjTf8FKSkps2fPrqysjFzeuNjIkSOd32FFPP/888aquPTSS6usLhtNmTLFuMXJkyeLbs5Fu3fvNh2Q8+bNi29Ve/bsSUtLM67q4osvPnnypHGZAwcOmDZnRyE845VXXjGW/dFHH3V7jzyJRCaHRCaHUCbKVFGEMhsRyuTEdNwSymxEIosPiUwOicxhhDI51K0taBPkcC5zER2wuJkqjdRgI9KunJiOW+sYpWF0UQ6j4nK4muMkEpktSGRySGTuIpTFzVRphDIbEcrkxHTcWqd5KCORySGRySGRacu3bTHgPxMnTjR1F7p06bJq1Sp7t7J79+7hw4ebNnTTTTfZuxWllJeXm35C/de//nVFRYWVzxYVFZ177rnGz/bp0yfK8sePHzc9CiJgXxdcNZWVlV26dDGWtF27ditXroxcsqysbNq0acnJyYEItWrVWrZsmZXNmb4gDRs2LC4utrlIKhE9iiorK9esWTNx4sSuXbtG/qcE/BvkQk6cOHHGGWeYinzLLbfk5eVV95FHH33UuPC4ceNKS0ujb6WiomLatGmmrYwbN87u0qjFVN7LL7/8z3/+88svv7xq1ar9+/ebhh2PHj3aokWL8MJjxoyJaVsff/yxcVt169YtKCiwtTSetGDBAlPqCwQCl1xySU5OjmlJ4wI6D/hGPlNNdFBg165dDRs2NG7Or52EkD59+pi+p//85z/jW9Vzzz1n+p8aNmxYWVlZeAGtLrBFysvLM5adq8JxI5EJIZHJIZSJEj2QCGWEMiGm8hLKHEYiixWJTBSJzEmEMjnUrV1oE4RwLnMdHbA4mKqL1GAj0q4cU3kZpbELo4tyGBUXxdUcx5DI7EIiE0IiUwGhLA6m6iKU2YhQJsdUXkKZLUhkckhkokhkevJtWwz4T1FRUZW/3N2/f/8FCxYkmAdKS0uXLFly1VVXGZ/vEtK2bdvDhw/bVQo1vfDCC6ZSDxs2rMZS79u3r3///qYPvvzyy1UuXFlZuXLlyjPPPNO0/PDhwwUKpIr58+ebypuUlHTrrbeuWbPmyJEjp06d2r9//xtvvHHOOecYl0lNTU1PTw+/rV+//kcffRRlK5WVlZEPepkyZYpjxXSFqbxyndQdO3bMmjVryJAh9erVC29OaFvq+OqrryJDWkpKyvjx49evXx8ZP0pLS0eMGGFc+Pzzz1+/fn1161+/fv3FF19sWn/Lli1939gGokpNTe3Ro8eoUaMmTpw4d+7cTz/99IknnjAuMG3aNIsbev3111NSUoyfHTFihGjRPGTHjh19+/Y1VX6jRo1ee+0142LGf9V8wNf0aMBAIPCHP/xBYtglJyfH9NSxHj162L4Vpbz55puRTcE111yzcePGONYWOYJz/vnnh8+PWl1gq5Lx8YFcFY4biUwOiUwOoUyOqbyEMnsRyoQEoiKUOYBEFisSmRwSmcMIZXKoW1vQJsjhXOY6OmCximwNjEgNCSLtCjEVmVEaGzG6KIdRcTlczXESicwWJDI5JDIVEMpiFdkgGBHKEkQoE2IqMqHMLiQyOSQyOSQyPfm5LQb8Z9WqVaYkEJacnNyrV6/bb7/95ZdfXr58+ZYtW6I03MXFxdu3b1+5cuXChQvvvffefv36paamVrfaL7/80skyuqKsrMz0I+mBQKBZs2aPPfZYbm5u5PK7d+9+4IEHGjRoYPpIly5dysvLTQuXlJTcd9997dq1i6zelJSU77//3pEiuqO8vLxfv35VHlpRzJo165lnnjH+pXbt2jfffPOOHTtM6w912i644ALTGurVq+f7voWpyA48PaW8vHz9+vVPPPHElVdeKb0tFTz33HNJSUlVHqJNmjT59a9//eSTT77//vubN28uKioKBoPl5eU333yzacl+/frNmDHjww8/XL9+/bp16z744IOpU6dGjrWFLF261O1Ci4uhIahGjWNnOTk59957r+n/Ljk52d9PGIpVWVnZww8/XLt2bVP1XnPNNUeOHAktY/y75gO+a9eujTwUMzMzb7311g8//HDnzp0FBQWRZ/+YnDp1av78+U2bNjVt5emnn7arFMoaM2ZMlV/2s846a8KECXPnzl22bJnF623Hjh2LHMepU6fOnXfe+emnn+7Zs8f0T9JFU83IkSPDZeeqcCJIZEJIZHIIZXJMRSaU2Y5QJiGGhqAahLLEkchiQiITRSJzEqFMDnVrF9oEIZzLVEAHLCZVNgUxITVER9qVYCoyozQ2YnRRDqPioria4xgSmV1IZEJIZIoglMWkytYgJoSy6AhlEkxFJpTZhUQmh0QmikSmIZ/nCsB/VqxYkZaWFqU/YVS7du2MjIymTZu2adOmTZs2zZo1q1evXp06dSx+vGHDhh9++KHbJXbIt99+a3xAiFG3bt1GjRo1fvz4G2+8cdiwYe3bt6/ulLZy5crINR86dKi6Gq7uIRl+snfv3iZNmlg85AKBwKBBgyoqKioqKqoMaVlZWb/97W/vvffeu+66a8yYMZmZmVWu5J///Kfb5RZnKrImgwIOe+uttyy2t7Vq1apfv37Lli2tH+pGdevWXbhwodvFdUJ89WPUpUuX6lb+9ddfjxgxInIQMxAI3H333U4W0yvWrl0b+VyiNm3aLF++PMiA7//ffffdF/3I7NevX6zrzMnJWbVq1fz582+44YYWLVpErvO8884rKyuTKI5S8vLyqjubGw9Li2vbvXt3mzZtqlxJ5COyRMuloPvvvz9cdq4KJ4hEJoREJodQJsRUZEKZBEKZ7eKrHyNCmV1IZNaRyOSQyJxEKJND3dqFNkEO5zJF0AGzKPrhagWpoUakXduZCs4ojb0YXZTDqLgoruY4g0RmFxKZHBKZOghlFkU/Yq0glNWIUGY7U8EJZTYikckhkYkikenG/7kC8J9169b94he/sNjUxq179+7bt293u6yO+uCDD6pMXBbNnTu3ytVW2b2oVavWM88843AB3ZKdnd26dWsrdfjLX/7y0KFDoU/98MMP1T3WIrpbb73V3fI6w1RqgpyQDRs2RD4Ux17NmjVbs2aN2wV1yD333DN8+PCsrKz4vt2BqANnDz30UJUf6dmz5/Hjx50spocUFBTccMMNphpLSkqaMGGC8S+aD/gGg8GKigrjo14jxXGhYsCAAVFW2KBBg927dwsURUW7d+/u3r17lNqwfoEtGAz++OOP1V1jM5ErkZr+/ve/p/zPzJkz3d4dzyORCSGRySGUSTCVmlAmhFBmL0KZUkhkFpHIRJHIHEMok0Pd2og2QQjnMnXQAbOC1OAM0q69TGVnlMZ2jC7KYVRcFFdzHEAis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width="600" alt />
-<p class="caption">Figure 11: test.fastq2_LAGGING_0</p>
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width="600" alt />
+<p class="caption">Figure 11: test.fastq2_LEADING_16</p>
 </div>
 </center>
 <p><br /><br /></p>
 </center>
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width="600" alt />
-<p class="caption">Figure 12: test.fastq2_LEADING_16</p>
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width="600" alt />
+<p class="caption">Figure 12: test.fastq2_LAGGING_16</p>
 </div>
 </center>
 <p><br /><br /></p>
@@ -3390,7 +3390,7 @@ Sum
 </center>
 <p><br /><br /></p>
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width="600" alt />
 <p class="caption">Figure 21: Insertion site usage zoomed for sites with few insertions (total insertions).</p>
 </div>
 </center>
@@ -3444,23 +3444,127 @@ Sum
 <div id="backup" class="section level3">
 <h3>Backup</h3>
 <p>See the <a href="./reports">reports</a> folder for all the details of the analysis, including the parameters used in the .config file</p>
-<p><br /><br /></p>
 <p>Full .nextflow.log is in: /mnt/c/Users/Gael/Documents/Git_projects/14985_loot<br />The one in the <a href="./reports">reports</a> folder is not complete (miss the end)</p>
 <p><br /><br /></p>
 </div>
 <div id="workflow-version" class="section level3">
 <h3>Workflow Version</h3>
-<p>Project (empty means no .git folder where the main.nf file is present): loot <a href="https://gitlab.pasteur.fr/gmillot/14985_loot" class="uri">https://gitlab.pasteur.fr/gmillot/14985_loot</a> (fetch) <br />Git info (empty means no .git folder where the main.nf file is present): v7.7.0-dirty <br />Cmd line: nextflow run main.nf -resume <br />execution mode: local <br />Manifest’s pipeline version: null <br />result path: /mnt/c/Users/Gael/Documents/Git_projects/14985_loot/results/20220120_res_CL14985_B4985_4_1645559065 <br />nextflow version: 21.04.2</p>
+<div id="general" class="section level4">
+<h4>GENERAL</h4>
+<table>
+<colgroup>
+<col width="50%"></col>
+<col width="50%"></col>
+</colgroup>
+<thead>
+<tr class="header">
+<th align="left">Variable</th>
+<th align="left">Value</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td align="left">Project<br />(empty means no .git folder where the main.nf file is present)</td>
+<td align="left">loot <a href="https://gitlab.pasteur.fr/gmillot/14985_loot" class="uri">https://gitlab.pasteur.fr/gmillot/14985_loot</a> (fetch)</td>
+</tr>
+<tr class="even">
+<td align="left">Git info<br />(empty means no .git folder where the main.nf file is present)</td>
+<td align="left">v7.9.0-dirty</td>
+</tr>
+<tr class="odd">
+<td align="left">Cmd line</td>
+<td align="left">nextflow run main.nf -resume</td>
+</tr>
+<tr class="even">
+<td align="left">execution mode</td>
+<td align="left">local</td>
+</tr>
+<tr class="odd">
+<td align="left">Manifest’s pipeline version</td>
+<td align="left">null</td>
+</tr>
+<tr class="even">
+<td align="left">result path</td>
+<td align="left">/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/results/20220120_test_1645716342</td>
+</tr>
+<tr class="odd">
+<td align="left">nextflow version</td>
+<td align="left">21.04.2</td>
+</tr>
+</tbody>
+</table>
 <p><br /><br /></p>
-<p>IMPLICIT VARIABLES:</p>
-<p>launchDir (directory where the workflow is run): /mnt/c/Users/Gael/Documents/Git_projects/14985_loot<br /> projectDir (directory where the main.nf script is located): /mnt/c/Users/Gael/Documents/Git_projects/14985_loot<br /> workDir (directory where tasks temporary files are created): /mnt/c/Users/Gael/Documents/Git_projects/14985_loot/work</p>
+</div>
+<div id="implicit-variables" class="section level4">
+<h4>IMPLICIT VARIABLES</h4>
+<table>
+<colgroup>
+<col width="33%"></col>
+<col width="33%"></col>
+<col width="33%"></col>
+</colgroup>
+<thead>
+<tr class="header">
+<th align="left">Name</th>
+<th align="left">Description</th>
+<th align="left">Value</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td align="left">launchDir</td>
+<td align="left">Directory where the workflow is run</td>
+<td align="left">/mnt/c/Users/Gael/Documents/Git_projects/14985_loot</td>
+</tr>
+<tr class="even">
+<td align="left">nprojectDir</td>
+<td align="left">Directory where the main.nf script is located</td>
+<td align="left">/mnt/c/Users/Gael/Documents/Git_projects/14985_loot</td>
+</tr>
+<tr class="odd">
+<td align="left">workDir</td>
+<td align="left">Directory where tasks temporary files are created</td>
+<td align="left">/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/work</td>
+</tr>
+</tbody>
+</table>
 <p><br /><br /></p>
-<p>USER VARIABLES:<br /></p>
-<p>out_path: /mnt/c/Users/Gael/Documents/Git_projects/14985_loot/results/20220120_res_CL14985_B4985_4_1645559065<br /> in_path: /mnt/c/Users/Gael/Documents/Git_projects/14985_loot/dataset</p>
+</div>
+<div id="user-variables" class="section level4">
+<h4>USER VARIABLES</h4>
+<table>
+<colgroup>
+<col width="33%"></col>
+<col width="33%"></col>
+<col width="33%"></col>
+</colgroup>
+<thead>
+<tr class="header">
+<th align="left">Name</th>
+<th align="left">Description</th>
+<th align="left">Value</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td align="left">out_path</td>
+<td align="left">output folder path</td>
+<td align="left">/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/results/20220120_test_1645716342</td>
+</tr>
+<tr class="even">
+<td align="left">in_path</td>
+<td align="left">input folder path</td>
+<td align="left">/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/dataset</td>
+</tr>
+</tbody>
+</table>
 <p><br /><br /></p>
-<p>WORKFLOW DIAGRAM:<br /></p>
+</div>
+<div id="workflow-diagram" class="section level4">
+<h4>WORKFLOW DIAGRAM</h4>
 <p>See the <a href="./reports/nf_dag.png">nf_dag.png</a> file</p>
 </div>
+</div>
 
 
 
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/base_freq_report.txt b/example_of_result/20220120_test_1645716342/reports/base_freq_report.txt
similarity index 100%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/base_freq_report.txt
rename to example_of_result/20220120_test_1645716342/reports/base_freq_report.txt
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/bowtie2_report.txt b/example_of_result/20220120_test_1645716342/reports/bowtie2_report.txt
similarity index 97%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/bowtie2_report.txt
rename to example_of_result/20220120_test_1645716342/reports/bowtie2_report.txt
index 0245b07296076d62dfefca7cc0e067bb30b7a793..ba99390478fe49c60c9621ca5eb71f9cbfb0440e 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/bowtie2_report.txt
+++ b/example_of_result/20220120_test_1645716342/reports/bowtie2_report.txt
@@ -67,7 +67,7 @@ Getting block 1 of 1
   No samples; assembling all-inclusive block
   Sorting block of length 4641652 for bucket 1
   (Using difference cover)
-  Sorting block time: 00:00:00
+  Sorting block time: 00:00:01
 Returning block of 4641653 for bucket 1
 Exited Ebwt loop
 fchr[A]: 0
@@ -150,7 +150,7 @@ Getting block 1 of 1
   No samples; assembling all-inclusive block
   Sorting block of length 4641652 for bucket 1
   (Using difference cover)
-  Sorting block time: 00:00:00
+  Sorting block time: 00:00:01
 Returning block of 4641653 for bucket 1
 Exited Ebwt loop
 fchr[A]: 0
@@ -189,7 +189,7 @@ Headers:
     ebwtTotSz: 1547264
     color: 0
     reverse: 1
-Total time for backward call to driver() for mirror index: 00:00:00
+Total time for backward call to driver() for mirror index: 00:00:01
 
 
 <br /><br />
@@ -200,15 +200,15 @@ Total time for backward call to driver() for mirror index: 00:00:00
 Time loading reference: 00:00:00
 Time loading forward index: 00:00:00
 Time loading mirror index: 00:00:00
-Multiseed full-index search: 00:00:00
+Multiseed full-index search: 00:00:01
 3742 reads; of these:
   3742 (100.00%) were unpaired; of these:
     1240 (33.14%) aligned 0 times
     2308 (61.68%) aligned exactly 1 time
     194 (5.18%) aligned >1 times
 66.86% overall alignment rate
-Time searching: 00:00:00
-Overall time: 00:00:00
+Time searching: 00:00:01
+Overall time: 00:00:01
 
 
 <br /><br />
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/cov_report.txt b/example_of_result/20220120_test_1645716342/reports/cov_report.txt
similarity index 100%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/cov_report.txt
rename to example_of_result/20220120_test_1645716342/reports/cov_report.txt
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/dup_report.txt b/example_of_result/20220120_test_1645716342/reports/dup_report.txt
similarity index 100%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/dup_report.txt
rename to example_of_result/20220120_test_1645716342/reports/dup_report.txt
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/extract_seq_report.txt b/example_of_result/20220120_test_1645716342/reports/extract_seq_report.txt
similarity index 100%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/extract_seq_report.txt
rename to example_of_result/20220120_test_1645716342/reports/extract_seq_report.txt
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/final_insertion_files_report.txt b/example_of_result/20220120_test_1645716342/reports/final_insertion_files_report.txt
similarity index 97%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/final_insertion_files_report.txt
rename to example_of_result/20220120_test_1645716342/reports/final_insertion_files_report.txt
index d502970f964254969d17f3338aef4f4cc43fb5ea..d8cc9f99f1eb66969ffddf7ca35d5989905c5b3e 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/final_insertion_files_report.txt
+++ b/example_of_result/20220120_test_1645716342/reports/final_insertion_files_report.txt
@@ -12,7 +12,7 @@
 
 
 
-2022-02-22 20:41:51
+2022-02-24 16:27:10
 
 
 
@@ -46,7 +46,7 @@ NUMBER OF OBS POSITIONS:
 
 
 
-END TIME: 2022-02-22 20:41:51
+END TIME: 2022-02-24 16:27:10
 
 
 
@@ -132,7 +132,7 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 20:41:51
+TIME: 2022-02-24 16:27:10
 
 TOTAL TIME LAPSE: 0S
 
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/global_logo_report.txt b/example_of_result/20220120_test_1645716342/reports/global_logo_report.txt
similarity index 93%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/global_logo_report.txt
rename to example_of_result/20220120_test_1645716342/reports/global_logo_report.txt
index 710a71143560abf47a787ef2fc8bfde250af6fbc..3fc7a3a5e3f43736e37ac3f8792f6653d45b3e3e 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/global_logo_report.txt
+++ b/example_of_result/20220120_test_1645716342/reports/global_logo_report.txt
@@ -12,7 +12,7 @@
 
 
 
-2022-02-22 20:43:05
+2022-02-24 16:29:20
 
 
 
@@ -31,7 +31,7 @@
 
 
 
-END TIME: 2022-02-22 20:43:09
+END TIME: 2022-02-24 16:29:24
 
 
 
@@ -64,8 +64,8 @@ erase.objects      TRUE
 erase.graphs       TRUE 
 script             global_logo 
 run.way            SCRIPT 
-command            /usr/lib/R/bin/exec/R,--no-echo,--no-restore,--file=/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/bin/global_logo.R,--args,test.fastq2_LAGGING_0.stat test.fastq2_LEADING_16.stat test.fastq2_LAGGING_16.stat test.fastq2_LEADING_0.stat,test.fastq2,20,https://gitlab.pasteur.fr/gmillot/cute_little_R_functions/-/raw/v11.0.0/cute_little_R_functions.R,global_logo_report.txt 
-freq               test.fastq2_LAGGING_0.stat test.fastq2_LEADING_16.stat test.fastq2_LAGGING_16.stat test.fastq2_LEADING_0.stat 
+command            /usr/lib/R/bin/exec/R,--no-echo,--no-restore,--file=/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/bin/global_logo.R,--args,test.fastq2_LAGGING_0.stat test.fastq2_LEADING_0.stat test.fastq2_LEADING_16.stat test.fastq2_LAGGING_16.stat,test.fastq2,20,https://gitlab.pasteur.fr/gmillot/cute_little_R_functions/-/raw/v11.0.0/cute_little_R_functions.R,global_logo_report.txt 
+freq               test.fastq2_LAGGING_0.stat test.fastq2_LEADING_0.stat test.fastq2_LEADING_16.stat test.fastq2_LAGGING_16.stat 
 file_name          test.fastq2 
 insertion_dist     20 
 cute               https://gitlab.pasteur.fr/gmillot/cute_little_R_functions/-/raw/v11.0.0/cute_little_R_functions.R 
@@ -115,7 +115,7 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 20:43:09
+TIME: 2022-02-24 16:29:24
 
 TOTAL TIME LAPSE: 4S
 
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/insertion_report.txt b/example_of_result/20220120_test_1645716342/reports/insertion_report.txt
similarity index 100%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/insertion_report.txt
rename to example_of_result/20220120_test_1645716342/reports/insertion_report.txt
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/logo_report.txt b/example_of_result/20220120_test_1645716342/reports/logo_report.txt
similarity index 89%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/logo_report.txt
rename to example_of_result/20220120_test_1645716342/reports/logo_report.txt
index 6798ebbaedde1576f49ed9fc49526ba654c85ad8..7dbcd58e42f070debe61ebaacd723b47496e4ce8 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/logo_report.txt
+++ b/example_of_result/20220120_test_1645716342/reports/logo_report.txt
@@ -12,7 +12,7 @@
 
 
 
-2022-02-22 20:42:45
+2022-02-24 16:28:43
 
 
 
@@ -31,7 +31,7 @@
 
 
 
-END TIME: 2022-02-22 20:42:49
+END TIME: 2022-02-24 16:28:47
 
 
 
@@ -64,8 +64,8 @@ erase.objects      TRUE
 erase.graphs       TRUE 
 script             logo 
 run.way            SCRIPT 
-command            /usr/lib/R/bin/exec/R,--no-echo,--no-restore,--file=/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/bin/logo.R,--args,test.fastq2_LAGGING_16.stat,20,https://gitlab.pasteur.fr/gmillot/cute_little_R_functions/-/raw/v11.0.0/cute_little_R_functions.R,logo_report.txt 
-freq               test.fastq2_LAGGING_16.stat 
+command            /usr/lib/R/bin/exec/R,--no-echo,--no-restore,--file=/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/bin/logo.R,--args,test.fastq2_LAGGING_0.stat,20,https://gitlab.pasteur.fr/gmillot/cute_little_R_functions/-/raw/v11.0.0/cute_little_R_functions.R,logo_report.txt 
+freq               test.fastq2_LAGGING_0.stat 
 insertion_dist     20 
 cute               https://gitlab.pasteur.fr/gmillot/cute_little_R_functions/-/raw/v11.0.0/cute_little_R_functions.R 
 log                logo_report.txt
@@ -114,7 +114,7 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 20:42:49
+TIME: 2022-02-24 16:28:47
 
 TOTAL TIME LAPSE: 4S
 
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/motif_report.txt b/example_of_result/20220120_test_1645716342/reports/motif_report.txt
similarity index 96%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/motif_report.txt
rename to example_of_result/20220120_test_1645716342/reports/motif_report.txt
index a907b0f9f1a703c481291468ced131fd2b98dad4..9795dcbe11a7a7830ef6410690d14caea3886967 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/motif_report.txt
+++ b/example_of_result/20220120_test_1645716342/reports/motif_report.txt
@@ -12,7 +12,7 @@
 
 
 
-2022-02-22 15:19:47
+2022-02-24 16:26:56
 
 
 
@@ -78,12 +78,12 @@ fork and orient
 
 
 
-END TIME: 2022-02-22 15:20:10
+END TIME: 2022-02-24 16:27:04
 
 
 
 
-TOTAL TIME LAPSE: 23S
+TOTAL TIME LAPSE: 8S
 
 
 
@@ -168,9 +168,9 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 15:20:10
+TIME: 2022-02-24 16:27:04
 
-TOTAL TIME LAPSE: 23S
+TOTAL TIME LAPSE: 8S
 
 
 
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/multiqc_report.html b/example_of_result/20220120_test_1645716342/reports/multiqc_report.html
similarity index 99%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/multiqc_report.html
rename to example_of_result/20220120_test_1645716342/reports/multiqc_report.html
index efb976b9958c56eb7e00e1897b274b0e3024ebe1..7173cfe9cf388af573495bdafeda31184b366782 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/multiqc_report.html
+++ b/example_of_result/20220120_test_1645716342/reports/multiqc_report.html
@@ -6259,12 +6259,12 @@ function findPos(obj) {
 <div id="analysis_dirs_wrapper">
   <p>Report
   
-    generated on 2022-02-22, 20:41
+    generated on 2022-02-24, 16:26
   
   
     based on data in:
     
-      <code class="mqc_analysis_path">/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/work/94/21967ce4a85b02def4eb06915f6f80</code></p>
+      <code class="mqc_analysis_path">/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/work/93/1153d4999b615ba1588b10ad731538</code></p>
     
   
 </div>
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nextflow.config b/example_of_result/20220120_test_1645716342/reports/nextflow.config
similarity index 92%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nextflow.config
rename to example_of_result/20220120_test_1645716342/reports/nextflow.config
index 18806d4e654673e56512a9249e8a54064d699916..1354d0397f9f90bd27ca1086919b398ceb67ee9d 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nextflow.config
+++ b/example_of_result/20220120_test_1645716342/reports/nextflow.config
@@ -73,14 +73,14 @@ env {
 //////// variables that will be used below (and potentially in the main.nf file)
 
 //// must be also exported
-system_exec = 'local' // the system that runs the workflow. Either 'local' or 'slurm'
+system_exec = 'local' // the system that runs the workflow. Either 'local' or 'slurm' or 'slurm_local' (test using the head of the cluster)
 //docker_exe = true // true for docker and false for singularity
 //out_path="/mnt/c/Users/Gael/Desktop" // where the report file will be saved. Example report_path = '.' for where the main.nf run is executed or report_path = '/mnt/c/Users/Gael/Desktop' 
 out_path="$baseDir/results" // where the report file will be saved. Example report_path = '.' for where the main.nf run is executed or report_path = '/mnt/c/Users/Gael/Desktop' 
 //// end must be also exported
 
 //// general variables
-result_folder_name="20220120_res_CL14985_B4985_4"
+result_folder_name="20220120_test"
 //// end general variables
 
 //// slurm variables
@@ -159,16 +159,18 @@ dag {
 singularity {
     enabled = true
     autoMounts = true // automatically mounts host paths in the executed container
-    if(system_exec == 'slurm'){
+    if(system_exec == 'slurm' || system_exec == 'slurm_local'){
         runOptions = '--no-home --bind /pasteur'
     }else{
-        runOptions = '--no-home'
+        runOptions = '--no-home' // --no-home prevent singularity to mount the $HOME path and thus forces singularity to work with only what is inside the container
     }
     //runOptions = '--home $HOME:/home/$USER --bind /pasteur' // provide any extra command line options supported by the singularity exec. Here, fait un bind de tout /pasteur dans /pasteur du container. Sinon pas d accès
     if(system_exec == 'slurm'){
         cacheDir = '/pasteur/zeus/projets/p01/BioIT/gmillot/14985_loot/singularity' // name of the directory where remote Singularity images are stored. When rerun, the exec directly uses these without redownloading them. When using a computing cluster it must be a shared folder accessible to all computing nodes
+    }else if(system_exec == 'slurm_local'){
+        cacheDir = 'singularity' // "$baseDir/singularity" can be used but do not forget double quotes.
     }else{
-        cacheDir = 'singularity'
+        cacheDir = '/mnt/c/Users/Gael/Documents/singularity' // "$baseDir/singularity" can be used but do not forget double quotes.
     }
 }
 
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nf_dag.png b/example_of_result/20220120_test_1645716342/reports/nf_dag.png
similarity index 100%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nf_dag.png
rename to example_of_result/20220120_test_1645716342/reports/nf_dag.png
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nf_report.html b/example_of_result/20220120_test_1645716342/reports/nf_report.html
similarity index 95%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nf_report.html
rename to example_of_result/20220120_test_1645716342/reports/nf_report.html
index 3a56b4922d7f669e6888dce473c856bb708f67a2..f50a866671b2cd2b1a81836441c17edd38ff7875 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nf_report.html
+++ b/example_of_result/20220120_test_1645716342/reports/nf_report.html
@@ -18,11 +18,11 @@
 <head>
   <meta charset="utf-8">
   <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-  <meta name="description" content="Nextflow workflow report for run id [scruffy_euler]">
+  <meta name="description" content="Nextflow workflow report for run id [cheesy_heyrovsky]">
   <meta name="author" content="Paolo Di Tommaso, Phil Ewels">
   <link rel="icon" type="image/png" href="https://www.nextflow.io/img/favicon.png" />
 
-  <title>[scruffy_euler] Nextflow Workflow Report</title>
+  <title>[cheesy_heyrovsky] Nextflow Workflow Report</title>
 
   <style type="text/css">
   /*!
@@ -137,7 +137,7 @@ table.DTCR_clonedTable.dataTable{position:absolute !important;background-color:r
         <li class="nav-item"><a class="nav-link" href="#tasks">Tasks</a></li>
       </ul>
       <span class="navbar-text">
-        [scruffy_euler]
+        [cheesy_heyrovsky]
       </span>
     </div>
   </nav>
@@ -146,7 +146,7 @@ table.DTCR_clonedTable.dataTable{position:absolute !important;background-color:r
     <div class="container">
 
       <h1 class="display-3">Nextflow workflow report</h1>
-      <h2 class="text-muted mb-4"><samp>[scruffy_euler]</samp> <em>(resumed run)</em></h2>
+      <h2 class="text-muted mb-4"><samp>[cheesy_heyrovsky]</samp> <em>(resumed run)</em></h2>
 
       
           <div class="alert alert-success mb-4">
@@ -157,14 +157,14 @@ table.DTCR_clonedTable.dataTable{position:absolute !important;background-color:r
       <dl>
         <dt>Run times</dt>
         <dd>
-          <span id="workflow_start">22-Feb-2022 20:44:26</span> - <span id="workflow_complete">22-Feb-2022 20:44:40</span>
-          (<span id="completed_fromnow"></span>duration: <strong>14.8s</strong>)
+          <span id="workflow_start">24-Feb-2022 16:25:42</span> - <span id="workflow_complete">24-Feb-2022 16:30:11</span>
+          (<span id="completed_fromnow"></span>duration: <strong>4m 29s</strong>)
         </dd>
 
         <dl>
           <div class="progress" style="height: 1.6rem; margin: 1.2rem auto; border-radius: 0.20rem;">
-            <div style="width: 14.29%" class="progress-bar bg-success" data-toggle="tooltip" data-placement="top" title="6 tasks succeeded"><span class="text-truncate">&nbsp; 6 succeeded &nbsp;</span></div>
-            <div style="width: 85.71%" class="progress-bar bg-secondary" data-toggle="tooltip" data-placement="top" title="36 tasks were cached"><span class="text-truncate">&nbsp; 36 cached &nbsp;</span></div>
+            <div style="width: 100.0%" class="progress-bar bg-success" data-toggle="tooltip" data-placement="top" title="42 tasks succeeded"><span class="text-truncate">&nbsp; 42 succeeded &nbsp;</span></div>
+            <div style="width: 0.0%" class="progress-bar bg-secondary" data-toggle="tooltip" data-placement="top" title="0 tasks were cached"><span class="text-truncate">&nbsp; 0 cached &nbsp;</span></div>
             <div style="width: 0.0%" class="progress-bar bg-warning" data-toggle="tooltip" data-placement="top" title="0 tasks reported and error and were ignored"><span class="text-truncate">&nbsp; 0 ignored &nbsp;</span></div>
             <div style="width: 0.0%" class="progress-bar bg-danger" data-toggle="tooltip" data-placement="top" title="0 tasks failed"><span class="text-truncate">&nbsp; 0 failed &nbsp;</span></div>
           </div>
@@ -176,7 +176,7 @@ table.DTCR_clonedTable.dataTable{position:absolute !important;background-color:r
 
       <dl class="row small">
         <dt class="col-sm-3">CPU-Hours</dt>
-        <dd class="col-sm-9"><samp>0.1 (97.1% cached)</samp></dd>
+        <dd class="col-sm-9"><samp>0.1</samp></dd>
 
         <dt class="col-sm-3">Launch directory</dt>
         <dd class="col-sm-9"><samp>/mnt/c/Users/Gael/Documents/Git_projects/14985_loot</samp></dd>
@@ -194,7 +194,7 @@ table.DTCR_clonedTable.dataTable{position:absolute !important;background-color:r
 
         
           <dt class="col-sm-3">Script ID</dt>
-          <dd class="col-sm-9"><code>78f3efb37d46152fe4a1aae3833f58d7</code></dd>
+          <dd class="col-sm-9"><code>f3870e96ad8a0e4ccb297fbb71eb4459</code></dd>
         
 
         <dt class="col-sm-3">Workflow session</dt>
@@ -1029,7 +1029,7 @@ $(function() {
 
   // Nextflow report data
   window.data = { "trace":[
-{"task_id":"2","hash":"e7\/424ee9","native_id":"183","process":"Nremove","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"Nremove (1)","status":"CACHED","exit":"0","submit":"1645539554426","start":"1645539554480","complete":"1645539559269","duration":"4843","realtime":"1650","%cpu":"46.8","%mem":"0.0","rss":"12603392","vmem":"73981952","peak_rss":"12603392","peak_vmem":"73994240","rchar":"17604754","wchar":"15167114","syscr":"1863","syscw":"1271","read_bytes":"568320","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/e7\/424ee9987bd6cc15e9f9d936c0cc43","script":"\n    Nremove.sh test.fastq2.gz \"test.fastq2_Nremove.gz\" \"report.rmd\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645539550\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"970","inv_ctxt":"8"},{"task_id":"1","hash":"d1\/d3302b","native_id":"21389","process":"init","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"init","status":"COMPLETED","exit":"0","submit":"1645559067767","start":"1645559067819","complete":"1645559069517","duration":"1750","realtime":"12","%cpu":"6.2","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"106624","wchar":"669","syscr":"190","syscw":"26","read_bytes":"242688","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/d1\/d3302b2b95419a2bd746915699ca1c","script":"\n    echo \"---\n    title: \'Insertion Sites Report\'\n    author: \'Gael Millot\'\n    date: \'`r Sys.Date()`\'\n    output:\n      html_document:\n        toc: TRUE\n        toc_float: TRUE\n    ---\n\n    \\n\\n<br \/><br \/>\\n\\n\n    \" > report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645559065\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"4","hash":"5c\/9949b3","native_id":"1152","process":"trim","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-alien_trimmer_v0.4.0-gitlab_v8.1.img","tag":"-","name":"trim (1)","status":"CACHED","exit":"0","submit":"1645539559373","start":"1645539559469","complete":"1645539571656","duration":"12283","realtime":"9075","%cpu":"42.9","%mem":"0.1","rss":"65802240","vmem":"5908258816","peak_rss":"65802240","peak_vmem":"5970444288","rchar":"17145165","wchar":"12629476","syscr":"2381","syscw":"647","read_bytes":"9977856","write_bytes":"45056","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/5c\/9949b36aa24f474a2df13e02a07833","script":"\n    trim.sh test.fastq2_Nremove.gz \"test.fastq2_trim.fq\" 20200520_adapters_TruSeq_B2699_14985_CL.fasta 30 \"report.rmd\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645539550\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"3268","inv_ctxt":"3"},{"task_id":"7","hash":"1c\/07097b","native_id":"2902","process":"kraken","module":"-","container":"-","tag":"-","name":"kraken (1)","status":"CACHED","exit":"0","submit":"1645539571771","start":"1645539571856","complete":"1645539572156","duration":"385","realtime":"36","%cpu":"72.1","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"154384","wchar":"216","syscr":"228","syscw":"13","read_bytes":"49152","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/1c\/07097b4b20d1e7ff8808cce0189972","script":"\n        echo \"No kraken analysis performed in local running\" > test.fastq2_trim_kraken_std.txt\n        ","scratch":"-","queue":"-","cpus":"1","memory":"-","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645539550\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"3","hash":"6a\/b7ac99","native_id":"21417","process":"report1","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"report1","status":"COMPLETED","exit":"0","submit":"1645559067812","start":"1645559067844","complete":"1645559069685","duration":"1873","realtime":"18","%cpu":"6.0","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"106986","wchar":"683","syscr":"189","syscw":"54","read_bytes":"242688","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/6a\/b7ac99c6ef20f6ae94fd057eee7b64","script":"\n    echo -e \'\n\\n\\n<br \/><br \/>\\n\\n###  Read coverage\\n\\n\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 6: After Bowtie2 alignment](.\/figures\/plot_test.fastq2_bowtie2_mini.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 7: After Mapping Quality Q20 (1%) filtering](.\/figures\/plot_test.fastq2_q20_mini.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 8: After removal of reads with identical 5\' and 3\' coordinates](.\/figures\/plot_test.fastq2_q20_nodup_mini.png){width=600}\n\\n\\n<\/center>\\n\\n\n    \' > report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645559065\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"6","hash":"71\/e822e1","native_id":"1618","process":"fivep_filtering","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"fivep_filtering (1)","status":"CACHED","exit":"0","submit":"1645557048915","start":"1645557048986","complete":"1645557051955","duration":"3040","realtime":"1574","%cpu":"26.0","%mem":"0.0","rss":"10100736","vmem":"64393216","peak_rss":"10100736","peak_vmem":"64393216","rchar":"29336456","wchar":"16062031","syscr":"9150","syscw":"5787","read_bytes":"437248","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/71\/e822e1c9939386bf0005ec2fd48b82","script":"\n    fivep_filtering.sh test.fastq2_trim.fq \"test.fastq2\" \"^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\" 48 3 51 \"CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\" \"report.rmd\"\n    echo \"Nucleotide frequencies of the 5\' part of reads:\n\n\" >> report.rmd\n    echo \"\n\\`\\`\\`{r, echo = FALSE}\ntempo <- read.table(\'.\/files\/test.fastq2_5pAttc_1-51.stat\', header = TRUE, row.names = 1, colClasses = \'character\', sep = \'\\t\', check.names = FALSE) ; \nkableExtra::kable_styling(knitr::kable(head(tempo), row.names = TRUE, digits = 2, caption = NULL, format=\'html\'), c(\'striped\', \'bordered\', \'responsive\', \'condensed\'), font_size=10, full_width = FALSE, position = \'left\')\n\\`\\`\\`\n    \n\n\n    \" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645557046\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"1140","inv_ctxt":"1"},{"task_id":"5","hash":"01\/01ac2e","native_id":"2923","process":"fastqc1","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/evolbioinfo-fastqc-v0.11.8.img","tag":"-","name":"fastqc1 (1)","status":"CACHED","exit":"0","submit":"1645539571867","start":"1645539571955","complete":"1645539592209","duration":"20342","realtime":"17587","%cpu":"76.6","%mem":"0.2","rss":"205987840","vmem":"3289473024","peak_rss":"206073856","peak_vmem":"3342659584","rchar":"14605079","wchar":"1278925","syscr":"7610","syscw":"5170","read_bytes":"19988480","write_bytes":"712704","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/01\/01ac2e093748236317e68c0fcda7fc","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Read QC n\u00B01\\n\\n\" > report.rmd\n    echo -e \"Results are published in the [fastQC1](.\/fastQC1) folder\\n\\n\" >> report.rmd\n    fastqc test.fastq2_trim.fq | tee tempo.txt\n    cat tempo.txt >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"-","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645539550\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"4333","inv_ctxt":"3"},{"task_id":"8","hash":"74\/0a40f9","native_id":"2495","process":"cutoff","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"cutoff (1)","status":"CACHED","exit":"0","submit":"1645557052062","start":"1645557052156","complete":"1645557053756","duration":"1694","realtime":"632","%cpu":"19.5","%mem":"0.0","rss":"10084352","vmem":"64229376","peak_rss":"10084352","peak_vmem":"64229376","rchar":"7307957","wchar":"4049152","syscr":"2784","syscw":"2034","read_bytes":"384000","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/74\/0a40f972f4b09da1338accdb6fa740","script":"\n    cutoff.sh test.fastq2_5pAtccRm.fq 25 \"test.fastq2\" \"report.rmd\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645557046\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"1215","inv_ctxt":"0"},{"task_id":"10","hash":"d0\/cf0991","native_id":"8593","process":"plot_fivep_filtering_stat","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"plot_fivep_filtering_stat (1)","status":"CACHED","exit":"0","submit":"1645539707464","start":"1645539707524","complete":"1645539724346","duration":"16882","realtime":"15015","%cpu":"63.1","%mem":"0.2","rss":"213090304","vmem":"2617372672","peak_rss":"213090304","peak_vmem":"2617397248","rchar":"20034416","wchar":"836207","syscr":"4344","syscw":"399","read_bytes":"74364928","write_bytes":"24576","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/d0\/cf09910750ce431a619151f0ae6453","script":"\n    echo -e \"\n\\n\\n<br \/><br \/>\\n\\n###  Base frequencies at the 5\' extremity of reads\\n\\n\n\\n\\n<\/center>\\n\\n\n![Figure 1: Frequency of each base at the 5\' of the reads.](.\/figures\/plot_fivep_filtering_stat.png){width=600}\n\\n\\n<\/center>\\n\\n\n    \" > report.rmd\n    plot_fivep_filtering_stat.R \"test.fastq2_5pAttc_1-51.stat\" \"CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"plot_fivep_filtering_stat_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645539550\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"49036","inv_ctxt":"11"},{"task_id":"9","hash":"7a\/397d42","native_id":"4382","process":"fastqc2","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/evolbioinfo-fastqc-v0.11.8.img","tag":"-","name":"fastqc2 (1)","status":"CACHED","exit":"0","submit":"1645558039170","start":"1645558039254","complete":"1645558045426","duration":"6256","realtime":"5000","%cpu":"61.3","%mem":"0.1","rss":"157659136","vmem":"3289473024","peak_rss":"157745152","peak_vmem":"3342659584","rchar":"12869452","wchar":"1245410","syscr":"7419","syscw":"5119","read_bytes":"19984384","write_bytes":"688128","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/7a\/397d42d2b189282c77f4f71a1116b8","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Read QC n\u00B02\\n\\n\" > report.rmd\n    echo -e \"Results are published in the [fastQC2](.\/fastQC2) folder\\n\\n\" >> report.rmd\n    fastqc test.fastq2_5pAtccRm.fq | tee tempo.txt\n    cat tempo.txt >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"-","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558037\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"4346","inv_ctxt":"10"},{"task_id":"11","hash":"91\/8872f7","native_id":"10025","process":"bowtie2","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bowtie2_v2.3.4.3_extended_v2.0-gitlab_v8.0.img","tag":"-","name":"bowtie2 (1)","status":"CACHED","exit":"0","submit":"1645558859028","start":"1645558859117","complete":"1645558863236","duration":"4208","realtime":"3343","%cpu":"58.6","%mem":"0.0","rss":"64479232","vmem":"249081856","peak_rss":"117039104","peak_vmem":"251142144","rchar":"36678382","wchar":"17009938","syscr":"3391","syscw":"2514","read_bytes":"7209984","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/91\/8872f704ff4710085bb5f081a9cd78","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Bowtie2 indexing of the reference sequence\\n\\n\" >> bowtie2_report.txt\n    bowtie2-build Ecoli-K12-MG1655_ORI_CENTERED.fasta Ecoli-K12-MG1655_ORI_CENTERED |& tee -a bowtie2_report.txt\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Bowtie2 alignment\\n\\n\" > report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Bowtie2 alignment\\n\\n\" >> bowtie2_report.txt\n    bowtie2 --very-sensitive -x Ecoli-K12-MG1655_ORI_CENTERED -U test.fastq2_cutoff.fq -t -S test.fastq2_bowtie2.sam |& tee -a tempo.txt\n    # --very-sensitive: no soft clipping allowed and very sensitive seed alignment\n    # -t time displayed\n    cat tempo.txt >> bowtie2_report.txt\n    sed -i -e \':a;N;$!ba;s\/\\n\/\\n<br \\\/>\/g\' tempo.txt\n    cat tempo.txt >> report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n####  samtools conversion\\n\\n\" >> bowtie2_report.txt\n    # samtools faidx Ecoli-K12-MG1655_ORI_CENTERED.fasta\n    samtools view -bh -o tempo.bam test.fastq2_bowtie2.sam |& tee -a bowtie2_report.txt\n    samtools sort -o test.fastq2_bowtie2.bam tempo.bam |& tee -a bowtie2_report.txt\n    samtools index test.fastq2_bowtie2.bam |& tee -a bowtie2_report.txt\n    ","scratch":"-","queue":"-","cpus":"12","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"4244","inv_ctxt":"2"},{"task_id":"12","hash":"9d\/ad802f","native_id":"271","process":"motif","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"motif","status":"CACHED","exit":"0","submit":"1645539554758","start":"1645539554780","complete":"1645539612097","duration":"57339","realtime":"54369","%cpu":"45.6","%mem":"0.2","rss":"246657024","vmem":"2598617088","peak_rss":"246657024","peak_vmem":"2598641664","rchar":"50653025","wchar":"41640352","syscr":"6207","syscw":"34240","read_bytes":"32752640","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/9d\/ad802f7d525c8496c31e355d53bcbc","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n### Motif detection\\n\\n\" > report.rmd\n    echo -e \"\\n\\nThe forward motif is: G[AT]T\\n\\n\" >> report.rmd\n    echo -e \"\\n\\nThe reverse motif is: A[AT]C\\n\\n\" >> report.rmd\n    if [[ G[AT]T != \"NULL\" ]] ; then\n        cat Ecoli-K12-MG1655_ORI_CENTERED.fasta | sed \'1d\' | grep -Ebo \'G[AT]T\' > motif_fw.pos\n        cat Ecoli-K12-MG1655_ORI_CENTERED.fasta | sed \'1d\' | grep -Ebo \'A[AT]C\' > motif_rev.pos\n    else\n        cat Ecoli-K12-MG1655_ORI_CENTERED.fasta | sed \'1d\' | grep -Ebo \'[ACGT]\' > motif_fw.pos\n        cat Ecoli-K12-MG1655_ORI_CENTERED.fasta | sed \'1d\' | grep -Ebo \'[ACGT]\' > motif_rev.pos\n    fi\n    echo -e \"\nINDICATED POSITIONS IN FILES START AT ZERO AND CORRESPOND TO THE FIRST LEFT BASE OF THE MOTIF\n\"\n    motif.R \"motif_fw.pos\" \"motif_rev.pos\" \"2320711 2320942\" \"4627368 4627400\" \"4641652\" \"G[AT]T\" \"A[AT]C\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"motif_report.txt\" \"report.rmd\"\n\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645539550\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"59548","inv_ctxt":"452"},{"task_id":"14","hash":"3f\/736771","native_id":"21506","process":"backup","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"backup","status":"COMPLETED","exit":"0","submit":"1645559067976","start":"1645559068013","complete":"1645559069786","duration":"1810","realtime":"13","%cpu":"6.1","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"106844","wchar":"518","syscr":"189","syscw":"25","read_bytes":"242688","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/3f\/7367715b713eb5ed8096c95aaddbc5","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Backup\\n\\n\" > report.rmd\n    echo -e \"See the [reports](.\/reports) folder for all the details of the analysis, including the parameters used in the .config file\" >> report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\nFull .nextflow.log is in: \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot<br \/>The one in the [reports](.\/reports) folder is not complete (miss the end)\" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645559065\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"13","hash":"e7\/0f8ca5","native_id":"8799","process":"plot_read_length","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"plot_read_length (1)","status":"CACHED","exit":"0","submit":"1645558842125","start":"1645558842185","complete":"1645558859017","duration":"16892","realtime":"15626","%cpu":"67.1","%mem":"0.2","rss":"240742400","vmem":"2610106368","peak_rss":"322535424","peak_vmem":"2690592768","rchar":"20620729","wchar":"734696","syscr":"4655","syscw":"439","read_bytes":"74364928","write_bytes":"24576","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/e7\/0f8ca51abfd4baf7513f0d7bdf8e90","script":"\n    echo -e \'\n\\n\\n<br \/><br \/>\\n\\n###  Length of initial reads\\n\\n\n\\n\\n<\/center>\\n\\n\n![Figure 2: Frequency of reads according to read size (in bp).](.\/figures\/plot_read_length_ini.png){width=600}\n\\n\\n<\/center>\\n\\n\n\\n\\n<br \/><br \/>\\n\\n###  Length of reads after selection of attC in 5 prime \\n\\n\n\\n\\n<\/center>\\n\\n\n![Figure 3: Frequency of reads according to read size (in bp).](.\/figures\/plot_read_length_fivep_filtering.png){width=600}\n\\n\\n<\/center>\\n\\n\n\\n\\n<br \/><br \/>\\n\\n###  Length of reads after trimming \\n\\n\n\\n\\n<\/center>\\n\\n\n![Figure 4: Frequency of reads according to read size (in bp).](.\/figures\/plot_read_length_fivep_filtering_cut.png){width=600}\n\\n\\n<\/center>\\n\\n\n\\n\\n<br \/><br \/>\\n\\n###  Read length after cut-off\\n\\n\n\\n\\n<\/center>\\n\\n\n![Figure 5: Frequency of reads according to read size (in bp).](.\/figures\/plot_read_length_cutoff.png){width=600}\n\\n\\n<\/center>\\n\\n\n    \' > report.rmd\n    plot_read_length.R \"test.fastq2_ini.length\" \"test.fastq2_5pAttc.length\" \"test.fastq2_5pAtccRm.stat\" \"test.fastq2_cutoff.length\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"plot_read_length_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"72941","inv_ctxt":"73"},{"task_id":"17","hash":"70\/4547a0","native_id":"10486","process":"Q20","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-samtools_v1.14-gitlab_v8.0.img","tag":"-","name":"Q20 (1)","status":"CACHED","exit":"0","submit":"1645558863310","start":"1645558863352","complete":"1645558864866","duration":"1556","realtime":"375","%cpu":"17.2","%mem":"0.0","rss":"6107136","vmem":"44822528","peak_rss":"6107136","peak_vmem":"44830720","rchar":"3392025","wchar":"2260606","syscr":"888","syscw":"567","read_bytes":"1301504","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/70\/4547a0b6884d719647810fe5a038b4","script":"\n    samtools view -q 20 -b test.fastq2_bowtie2.bam > test.fastq2_q20.bam |& tee q20_report.txt\n    samtools index test.fastq2_q20.bam\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Q20 filtering\\n\\n\" > report.rmd\n    read_nb_before=$(samtools view test.fastq2_bowtie2.bam | wc -l | cut -f1 -d\' \') # -h to add the header\n    read_nb_after=$(samtools view test.fastq2_q20.bam | wc -l | cut -f1 -d\' \') # -h to add the header\n    echo -e \"\\n\\nNumber of sequences before Q20 filtering: $(printf \"%\'d\" ${read_nb_before})\\n\" >> report.rmd\n    echo -e \"\\n\\nNumber of sequences after Q20 filtering: $(printf \"%\'d\" ${read_nb_after})\\n\" >> report.rmd\n    echo -e \"Ratio: \" >> report.rmd\n    echo -e $(printf \"%.2f\n\" $(echo $\" $read_nb_after \/ $read_nb_before \" | bc -l)) >> report.rmd # the number in \'%.2f\\n\' is the number of decimals\n    echo -e \"\\n\\n\" >> report.rmd\n    echo $read_nb_before > read_nb_before # because nf cannot output values easily\n    echo $read_nb_after > read_nb_after\n    ","scratch":"-","queue":"-","cpus":"1","memory":"1073741824","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"879","inv_ctxt":"0"},{"task_id":"16","hash":"75\/97cb47","native_id":"10460","process":"coverage","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bedtools_v2.30.0-gitlab_v8.0.img","tag":"-","name":"coverage (1)","status":"CACHED","exit":"0","submit":"1645558863292","start":"1645558863337","complete":"1645558865297","duration":"2005","realtime":"809","%cpu":"15.7","%mem":"0.0","rss":"5365760","vmem":"46727168","peak_rss":"5365760","peak_vmem":"46727168","rchar":"491178","wchar":"93146","syscr":"251","syscw":"3116","read_bytes":"1806336","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/75\/97cb474869ed25f59b9bd63255debd","script":"\n    # bedtools genomecov -d -ibam ${bam} > ${bam.baseName}.cov |& tee cov_report.txt # coverage per base if ever required but long process\n    # to add the chr names | awk \'{h[$NF]++}; END { for(k in h) print k, h[k] }\' | sort -V > ${bam.baseName}.cov\n    bedtools genomecov -bga -ibam test.fastq2_bowtie2.bam  > test.fastq2_bowtie2_mini.cov |& tee cov_report.txt\n    # -g ${ref} not required when inputs are bam files\n    ","scratch":"-","queue":"-","cpus":"12","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"716","inv_ctxt":"0"},{"task_id":"15","hash":"8d\/8cfbe1","native_id":"21537","process":"workflowVersion","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"workflowVersion","status":"COMPLETED","exit":"0","submit":"1645559068024","start":"1645559068113","complete":"1645559070066","duration":"2042","realtime":"637","%cpu":"12.5","%mem":"0.0","rss":"5009408","vmem":"40304640","peak_rss":"5009408","peak_vmem":"40304640","rchar":"138244","wchar":"1712","syscr":"298","syscw":"53","read_bytes":"1465344","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/8d\/8cfbe1c9236cf36acf38b7d0f7a960","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Workflow Version\\n\\n\" > report.rmd\n    echo \"Project (empty means no .git folder where the main.nf file is present): \" $(git -C \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot remote -v | head -n 1) >> report.rmd # works only if the main script run is located in a directory that has a .git folder, i.e., that is connected to a distant repo\n    echo \"<br \/>Git info (empty means no .git folder where the main.nf file is present): \" $(git -C \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot describe --abbrev=10 --dirty --always --tags) >> report.rmd # idem. Provide the small commit number of the script and nextflow.config used in the execution\n    echo \"<br \/>Cmd line: nextflow run main.nf -resume\" >> report.rmd\n    echo \"<br \/>execution mode\": local >> report.rmd\n    modules= # this is just to deal with variable interpretation during the creation of the .command.sh file by nextflow. See also $modules below\n    if [[ ! -z $modules ]] ; then\n        echo \"<br \/>loaded modules (according to specification by the user thanks to the --modules argument of main.nf)\":  >> report.rmd\n    fi\n    echo \"<br \/>Manifest\'s pipeline version: null\" >> report.rmd\n    echo \"<br \/>result path: \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645559065\" >> report.rmd\n    echo \"<br \/>nextflow version: 21.04.2\" >> report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\nIMPLICIT VARIABLES:\\n\\nlaunchDir (directory where the workflow is run): \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot<br \/>\\nprojectDir (directory where the main.nf script is located): \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot<br \/>\\nworkDir (directory where tasks temporary files are created): \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\" >> report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\nUSER VARIABLES:<br \/>\\n\\nout_path: \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645559065<br \/>\\nin_path: \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\" >> report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\nWORKFLOW DIAGRAM:<br \/>\\n\\nSee the [nf_dag.png](.\/reports\/nf_dag.png) file\" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645559065\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"34","inv_ctxt":"3"},{"task_id":"18","hash":"94\/21967c","native_id":"10518","process":"multiQC","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/ewels-multiqc-1.10.1.img","tag":"-","name":"multiQC","status":"CACHED","exit":"0","submit":"1645558863330","start":"1645558863367","complete":"1645558871857","duration":"8527","realtime":"8000","%cpu":"40.2","%mem":"0.1","rss":"74358784","vmem":"85352448","peak_rss":"74358784","peak_vmem":"85352448","rchar":"29687055","wchar":"2404815","syscr":"9283","syscw":"289","read_bytes":"22943744","write_bytes":"1253376","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/94\/21967ce4a85b02def4eb06915f6f80","script":"\n    multiqc . -n multiqc_report.html\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  MultiQC\\n\\n\" > report.rmd\n    echo -e \"Results are published in the [Report](.\/reports\/multiqc_report.html) folder\\n\\n\" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"-","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"34333","inv_ctxt":"782"},{"task_id":"21","hash":"9b\/c9d978","native_id":"10927","process":"no_soft_clipping","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-samtools_v1.14-gitlab_v8.0.img","tag":"-","name":"no_soft_clipping (1)","status":"CACHED","exit":"0","submit":"1645558864907","start":"1645558864967","complete":"1645558866376","duration":"1469","realtime":"301","%cpu":"15.5","%mem":"0.0","rss":"3563520","vmem":"40296448","peak_rss":"3563520","peak_vmem":"40296448","rchar":"2188567","wchar":"1583809","syscr":"697","syscw":"417","read_bytes":"1152000","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/9b\/c9d978822144da7c93f35321e99a6f","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Control that no more soft clipping in reads\\n\\n\" > report.rmd\n    echo -e \"nb of reads with soft clipping (S) in CIGAR: $(printf \"%\'d\" $(samtools view test.fastq2_q20.bam | awk \'$6 ~ \/.*[S].*\/{print $0}\' | wc -l | cut -f1 -d\' \'))\" >> report.rmd\n    echo -e \"\\n\\ntotal nb of reads: $(printf \"%\'d\" $(samtools view test.fastq2_q20.bam | wc -l | cut -f1 -d\' \'))\" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"1073741824","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"29","inv_ctxt":"0"},{"task_id":"22","hash":"78\/6a3590","native_id":"11762","process":"plot_coverage","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"plot_coverage (1)","status":"CACHED","exit":"0","submit":"1645558867165","start":"1645558867256","complete":"1645558882617","duration":"15452","realtime":"14730","%cpu":"62.2","%mem":"0.2","rss":"213573632","vmem":"2620022784","peak_rss":"213573632","peak_vmem":"2620047360","rchar":"20065336","wchar":"475473","syscr":"4351","syscw":"303","read_bytes":"74364928","write_bytes":"24576","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/78\/6a3590d204f71a0dcaf525b5c0a32e","script":"\n    plot_coverage.R \"test.fastq2_bowtie2_mini\" \"read_nb_before\" \"2320711 2320942\" \"4627368 4627400\" \"5\" \"Ecoli Genome (bp)\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"plot_coverage_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"49155","inv_ctxt":"16"},{"task_id":"19","hash":"10\/b42e02","native_id":"11096","process":"coverage","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bedtools_v2.30.0-gitlab_v8.0.img","tag":"-","name":"coverage (2)","status":"CACHED","exit":"0","submit":"1645558865307","start":"1645558865396","complete":"1645558867156","duration":"1849","realtime":"741","%cpu":"16.5","%mem":"0.0","rss":"5292032","vmem":"46727168","peak_rss":"5292032","peak_vmem":"46727168","rchar":"343047","wchar":"84345","syscr":"239","syscw":"2824","read_bytes":"1734656","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/10\/b42e02b3664fd8dbe682962cfcee1e","script":"\n    # bedtools genomecov -d -ibam ${bam} > ${bam.baseName}.cov |& tee cov_report.txt # coverage per base if ever required but long process\n    # to add the chr names | awk \'{h[$NF]++}; END { for(k in h) print k, h[k] }\' | sort -V > ${bam.baseName}.cov\n    bedtools genomecov -bga -ibam test.fastq2_q20.bam  > test.fastq2_q20_mini.cov |& tee cov_report.txt\n    # -g ${ref} not required when inputs are bam files\n    ","scratch":"-","queue":"-","cpus":"12","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"621","inv_ctxt":"1"},{"task_id":"20","hash":"47\/ef2076","native_id":"10991","process":"duplicate_removal","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-samtools_v1.14-gitlab_v8.0.img","tag":"-","name":"duplicate_removal (1)","status":"CACHED","exit":"0","submit":"1645558864940","start":"1645558864987","complete":"1645558867876","duration":"2936","realtime":"1792","%cpu":"25.5","%mem":"0.0","rss":"7753728","vmem":"55619584","peak_rss":"7753728","peak_vmem":"55619584","rchar":"13465166","wchar":"6908304","syscr":"7201","syscw":"5706","read_bytes":"1376256","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/47\/ef2076cd3d9f7e403e795fe6bdbfec","script":"\n    duplicate_removal.sh test.fastq2_q20.bam Ecoli-K12-MG1655_ORI_CENTERED.fasta \"test.fastq2_q20_nodup.bam\" \"dup_report.txt\" \"report.rmd\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"1073741824","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"3216","inv_ctxt":"2"},{"task_id":"23","hash":"1a\/4b7041","native_id":"12101","process":"insertion","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-samtools_v1.14-gitlab_v8.0.img","tag":"-","name":"insertion (1)","status":"CACHED","exit":"0","submit":"1645558868884","start":"1645558868977","complete":"1645558870316","duration":"1432","realtime":"482","%cpu":"19.7","%mem":"0.0","rss":"9523200","vmem":"68771840","peak_rss":"9523200","peak_vmem":"68780032","rchar":"2612546","wchar":"1832054","syscr":"1550","syscw":"1165","read_bytes":"1236992","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/1a\/4b7041efd0c5f42fc6b1d707b34ae9","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n### Insertion positions\\n\\n\" > report.rmd\n    echo -e \"\\n\\nOne of the step is to correct insertion site read extremity for the reverse reads. It consist in the redefinition of POS according to FLAG in the bam file. See the [insertion_report.txt](.\/reports\/insertion_report.txt) file in the reports folders for details\\n\\n\" >> report.rmd\n    # extraction of bam column 2, 4 and 10, i.e., FALG, POS and SEQ\n    samtools view test.fastq2_q20_nodup.bam | awk \'BEGIN{FS=\"\\t\" ; OFS=\"\" ; ORS=\"\"}{print \">\"$2\"\\t\"$4\"\\n\"$10\"\\n\" }\' > tempo\n    # Of note, samtools fasta $DIR\/$SAMPLE_NAME > ${OUTPUT}.fasta # convert bam into fasta\n    echo -e \"\\n\\nExtraction of the FLAG (containing the read orientation) the POS and the SEQ of the bams\\nHeader is the 1) sens of insersion (0 or 16) and 2) insertion site position\\n\\n\" >> insertion_report.txt\n    cat tempo | head -60 | tail -20 >> insertion_report.txt\n    # redefinition of POS according to FLAG\n    awk \'BEGIN{FS=\"\t\" ; OFS=\"\" ; ORS=\"\"}{lineKind=(NR-1)%2}lineKind==0{orient=($1~\">16\") ; if(orient){var1 = $1 ; var2 = $2}else{print $0\"\\n\"}}lineKind==1{if(orient){var3 = length($0) ; var4 = var2 + var3 - 1 ; print var1\"\\t\"var4\"\\n\"$0\"\\n\"}else{print $0\"\\n\"}}\' tempo > test.fastq2_reorient.fasta\n    echo -e \"\\n\\nFinal fasta file\\n\\n\" >> insertion_report.txt\n    cat test.fastq2_reorient.fasta | head -60 | tail -20 >> insertion_report.txt\n    awk \'{lineKind=(NR-1)%2}lineKind==0{gsub(\/>\/, \"\", $1) ; print $0}\' test.fastq2_reorient.fasta > test.fastq2.pos\n    echo -e \"\\n\\nFinal pos file\\n\\n\" >> insertion_report.txt\n    cat test.fastq2.pos | head -60 | tail -20 >> insertion_report.txt\n\n    read_nb_before=$(samtools view test.fastq2_q20_nodup.bam | wc -l | cut -f1 -d\' \') # -h to add the header. Thus do not put here\n    read_nb_after=$(wc -l test.fastq2.pos | cut -f1 -d\' \')\n    echo -e \"\\n\\nNumber of reads used for insertion computation: $(printf \"%\'d\" ${read_nb_before})\\n\" >> report.rmd\n    echo -e \"\\n\\nNumber of insertions: $(printf \"%\'d\" ${read_nb_after})\\n\" >> report.rmd\n    echo -e \"Ratio: \" >> report.rmd\n    echo -e $(printf \"%.2f\n\" $(echo $\" $read_nb_after \/ $read_nb_before \" | bc -l)) >> report.rmd # the number in \'%.2f\\n\' is the number of decimals\n    echo -e \"\\n\\n\" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"1073741824","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"915","inv_ctxt":"0"},{"task_id":"25","hash":"2b\/d2a26d","native_id":"13051","process":"plot_coverage","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"plot_coverage (2)","status":"CACHED","exit":"0","submit":"1645558882625","start":"1645558882717","complete":"1645558897437","duration":"14812","realtime":"14131","%cpu":"64.5","%mem":"0.2","rss":"216543232","vmem":"2620534784","peak_rss":"216543232","peak_vmem":"2620559360","rchar":"20056617","wchar":"466811","syscr":"4353","syscw":"301","read_bytes":"74364928","write_bytes":"24576","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/2b\/d2a26dc2556edcdff2a3f9fbc617da","script":"\n    plot_coverage.R \"test.fastq2_q20_mini\" \"read_nb_after\" \"2320711 2320942\" \"4627368 4627400\" \"5\" \"Ecoli Genome (bp)\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"plot_coverage_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"49206","inv_ctxt":"9"},{"task_id":"24","hash":"5e\/1ca0b8","native_id":"13773","process":"coverage","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bedtools_v2.30.0-gitlab_v8.0.img","tag":"-","name":"coverage (3)","status":"CACHED","exit":"0","submit":"1645558897445","start":"1645558897537","complete":"1645558898902","duration":"1457","realtime":"578","%cpu":"19.7","%mem":"0.0","rss":"5332992","vmem":"46727168","peak_rss":"5332992","peak_vmem":"46727168","rchar":"317670","wchar":"84029","syscr":"235","syscw":"2820","read_bytes":"1806336","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/5e\/1ca0b8fd32e8df18805ebc0f96f5a7","script":"\n    # bedtools genomecov -d -ibam ${bam} > ${bam.baseName}.cov |& tee cov_report.txt # coverage per base if ever required but long process\n    # to add the chr names | awk \'{h[$NF]++}; END { for(k in h) print k, h[k] }\' | sort -V > ${bam.baseName}.cov\n    bedtools genomecov -bga -ibam test.fastq2_q20_nodup.bam  > test.fastq2_q20_nodup_mini.cov |& tee cov_report.txt\n    # -g ${ref} not required when inputs are bam files\n    ","scratch":"-","queue":"-","cpus":"12","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"805","inv_ctxt":"0"},{"task_id":"27","hash":"f6\/edb675","native_id":"13925","process":"seq_around_insertion","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"seq_around_insertion (1)","status":"CACHED","exit":"0","submit":"1645558898925","start":"1645558899001","complete":"1645558905256","duration":"6331","realtime":"5608","%cpu":"72.5","%mem":"0.1","rss":"164118528","vmem":"2516324352","peak_rss":"164118528","peak_vmem":"2516348928","rchar":"18784250","wchar":"234914","syscr":"2734","syscw":"362","read_bytes":"32610304","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/f6\/edb6752996bda63e72c1a7ac83117a","script":"\n    seq_around_insertion.R \"test.fastq2.pos\" \"2320711 2320942\" \"4627368 4627400\" \"20\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"seq_around_insertion_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"31251","inv_ctxt":"6"},{"task_id":"26","hash":"9e\/6e5dd6","native_id":"14430","process":"final_insertion_files","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"final_insertion_files (1)","status":"CACHED","exit":"0","submit":"1645558905265","start":"1645558905357","complete":"1645558911756","duration":"6491","realtime":"5750","%cpu":"72.1","%mem":"0.2","rss":"181882880","vmem":"2515492864","peak_rss":"181882880","peak_vmem":"2515517440","rchar":"18856269","wchar":"272413","syscr":"2790","syscw":"510","read_bytes":"32802816","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/9e\/6e5dd6b9f8d5957936a0c64405d265","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Final insertion site files\\n\\n\" > report.rmd\n    echo -e \"\\n\\nSee the [test.fastq2_annot.pos](.\/files\/test.fastq2_annot.pos) and [test.fastq2_annot.freq](.\/files\/test.fastq2_annot.freq) files\\n\\n\" >> report.rmd\n    final_insertion_files.R \"test.fastq2.pos\" \"2320711 2320942\" \"4627368 4627400\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"final_insertion_files_report.txt\"\n    pos_nb=$(wc -l test.fastq2_annot.pos | cut -f1 -d\' \')\n    echo -e \"\\n\\nNumber of different positions: $(printf \"%\'d\" ${pos_nb})\\n\" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"31094","inv_ctxt":"1"},{"task_id":"28","hash":"55\/2b9806","native_id":"14883","process":"plot_coverage","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"plot_coverage (3)","status":"CACHED","exit":"0","submit":"1645558911764","start":"1645558911856","complete":"1645558926747","duration":"14983","realtime":"14303","%cpu":"63.9","%mem":"0.2","rss":"216424448","vmem":"2620596224","peak_rss":"216424448","peak_vmem":"2620620800","rchar":"20056220","wchar":"470110","syscr":"4347","syscw":"302","read_bytes":"74364928","write_bytes":"24576","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/55\/2b9806394422b358eadd7deddca6fc","script":"\n    plot_coverage.R \"test.fastq2_q20_nodup_mini\" \"dup_read_nb\" \"2320711 2320942\" \"4627368 4627400\" \"5\" \"Ecoli Genome (bp)\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"plot_coverage_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"49193","inv_ctxt":"4"},{"task_id":"29","hash":"ef\/0f9c22","native_id":"15606","process":"extract_seq","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bedtools_v2.30.0-gitlab_v8.0.img","tag":"-","name":"extract_seq (1)","status":"CACHED","exit":"0","submit":"1645558926756","start":"1645558926847","complete":"1645558928466","duration":"1710","realtime":"840","%cpu":"19.6","%mem":"0.0","rss":"6078464","vmem":"52637696","peak_rss":"6078464","peak_vmem":"52654080","rchar":"9503035","wchar":"4763828","syscr":"866","syscw":"3344","read_bytes":"6359040","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/ef\/0f9c2238b3a6a5fb96f6863dc52f76","script":"\n    # make a bed file from the reference genome\n    echo \">ref\" > tempo.ref.fasta\n    awk \'{lineKind=(NR-1)%2}lineKind==1{print $0}\' Ecoli-K12-MG1655_ORI_CENTERED.fasta >> tempo.ref.fasta |& tee extract_seq_report.txt\n    bedtools getfasta -fi tempo.ref.fasta -bed test.fastq2_around_insertion.bed -fo \"test.fastq2_around_insertion.fasta\" -name |& tee extract_seq_report.txt\n    rm tempo.ref.fasta\n    rm tempo.ref.fasta.fai\n    ","scratch":"-","queue":"-","cpus":"12","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"555","inv_ctxt":"0"},{"task_id":"34","hash":"93\/91ac2a","native_id":"15899","process":"base_freq","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"base_freq (1)","status":"CACHED","exit":"0","submit":"1645558928578","start":"1645558928666","complete":"1645558930238","duration":"1660","realtime":"91","%cpu":"13.5","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"286262","wchar":"17180","syscr":"526","syscw":"46","read_bytes":"279552","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/93\/91ac2a51a51a86700a55f190ca1e8d","script":"\n    # file splitting into seq\n    awk -v var1=LEADING_0 \'\n        {lineKind=(NR-1)%2}\n        lineKind==0{toGet=($0 ~ \">\" var1) ; next}\n        lineKind==1{if(toGet){print $0}}\n        \' test.fastq2_around_insertion.fasta > test.fastq2_LEADING_0.seq |& tee base_freq_report.txt\n    # ATGC contingency\n    gawk \'{\n        L=length($0);\n        for(i=1;i<=L;i++) {\n            B=substr($0,i,1);\n            T[i][B]++;\n        }\n      }\n      END{\n            for(BI=0;BI<5;BI++) {\n                B=(BI==0?\"A\":(BI==1?\"C\":(BI==2?\"G\":(BI==3?\"T\":\"Other\"))));\n                printf(\"%s\",B); \n                for(i in T) {\n                    tot=0.0;\n                    for(B2 in T[i]){\n                        tot+=T[i][B2];\n                    }\n                printf(\"\t%0.5f\",(T[i][B])); # T[i][B]\/tot for proportion\n                } \n            printf(\"\\n\");\n            }\n    }\' test.fastq2_LEADING_0.seq > test.fastq2_LEADING_0.stat |& tee base_freq_report.txt\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"33","hash":"9e\/88bce3","native_id":"15833","process":"base_freq","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"base_freq (4)","status":"CACHED","exit":"0","submit":"1645558928530","start":"1645558928577","complete":"1645558930226","duration":"1696","realtime":"102","%cpu":"11.5","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"288564","wchar":"19499","syscr":"531","syscw":"51","read_bytes":"279552","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/9e\/88bce328f319e90a6bfdec34e54916","script":"\n    # file splitting into seq\n    awk -v var1=LAGGING_16 \'\n        {lineKind=(NR-1)%2}\n        lineKind==0{toGet=($0 ~ \">\" var1) ; next}\n        lineKind==1{if(toGet){print $0}}\n        \' test.fastq2_around_insertion.fasta > test.fastq2_LAGGING_16.seq |& tee base_freq_report.txt\n    # ATGC contingency\n    gawk \'{\n        L=length($0);\n        for(i=1;i<=L;i++) {\n            B=substr($0,i,1);\n            T[i][B]++;\n        }\n      }\n      END{\n            for(BI=0;BI<5;BI++) {\n                B=(BI==0?\"A\":(BI==1?\"C\":(BI==2?\"G\":(BI==3?\"T\":\"Other\"))));\n                printf(\"%s\",B); \n                for(i in T) {\n                    tot=0.0;\n                    for(B2 in T[i]){\n                        tot+=T[i][B2];\n                    }\n                printf(\"\t%0.5f\",(T[i][B])); # T[i][B]\/tot for proportion\n                } \n            printf(\"\\n\");\n            }\n    }\' test.fastq2_LAGGING_16.seq > test.fastq2_LAGGING_16.stat |& tee base_freq_report.txt\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"32","hash":"dd\/d59b9f","native_id":"15868","process":"base_freq","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"base_freq (3)","status":"CACHED","exit":"0","submit":"1645558928560","start":"1645558928589","complete":"1645558929976","duration":"1416","realtime":"103","%cpu":"12.1","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"289213","wchar":"20167","syscr":"532","syscw":"52","read_bytes":"279552","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/dd\/d59b9f6cbd5cf7096a07b21239bac3","script":"\n    # file splitting into seq\n    awk -v var1=LAGGING_0 \'\n        {lineKind=(NR-1)%2}\n        lineKind==0{toGet=($0 ~ \">\" var1) ; next}\n        lineKind==1{if(toGet){print $0}}\n        \' test.fastq2_around_insertion.fasta > test.fastq2_LAGGING_0.seq |& tee base_freq_report.txt\n    # ATGC contingency\n    gawk \'{\n        L=length($0);\n        for(i=1;i<=L;i++) {\n            B=substr($0,i,1);\n            T[i][B]++;\n        }\n      }\n      END{\n            for(BI=0;BI<5;BI++) {\n                B=(BI==0?\"A\":(BI==1?\"C\":(BI==2?\"G\":(BI==3?\"T\":\"Other\"))));\n                printf(\"%s\",B); \n                for(i in T) {\n                    tot=0.0;\n                    for(B2 in T[i]){\n                        tot+=T[i][B2];\n                    }\n                printf(\"\t%0.5f\",(T[i][B])); # T[i][B]\/tot for proportion\n                } \n            printf(\"\\n\");\n            }\n    }\' test.fastq2_LAGGING_0.seq > test.fastq2_LAGGING_0.stat |& tee base_freq_report.txt\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"31","hash":"82\/5592cb","native_id":"15942","process":"base_freq","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"base_freq (2)","status":"CACHED","exit":"0","submit":"1645558928599","start":"1645558928676","complete":"1645558930056","duration":"1457","realtime":"97","%cpu":"11.6","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"288398","wchar":"19342","syscr":"530","syscw":"50","read_bytes":"279552","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/82\/5592cb0f173df9bb955ca03f13127a","script":"\n    # file splitting into seq\n    awk -v var1=LEADING_16 \'\n        {lineKind=(NR-1)%2}\n        lineKind==0{toGet=($0 ~ \">\" var1) ; next}\n        lineKind==1{if(toGet){print $0}}\n        \' test.fastq2_around_insertion.fasta > test.fastq2_LEADING_16.seq |& tee base_freq_report.txt\n    # ATGC contingency\n    gawk \'{\n        L=length($0);\n        for(i=1;i<=L;i++) {\n            B=substr($0,i,1);\n            T[i][B]++;\n        }\n      }\n      END{\n            for(BI=0;BI<5;BI++) {\n                B=(BI==0?\"A\":(BI==1?\"C\":(BI==2?\"G\":(BI==3?\"T\":\"Other\"))));\n                printf(\"%s\",B); \n                for(i in T) {\n                    tot=0.0;\n                    for(B2 in T[i]){\n                        tot+=T[i][B2];\n                    }\n                printf(\"\t%0.5f\",(T[i][B])); # T[i][B]\/tot for proportion\n                } \n            printf(\"\\n\");\n            }\n    }\' test.fastq2_LEADING_16.seq > test.fastq2_LEADING_16.stat |& tee base_freq_report.txt\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"30","hash":"ef\/14c394","native_id":"15793","process":"random_insertion","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"random_insertion (1)","status":"CACHED","exit":"0","submit":"1645558928476","start":"1645558928566","complete":"1645558941597","duration":"13121","realtime":"12103","%cpu":"61.6","%mem":"0.4","rss":"402747392","vmem":"2905137152","peak_rss":"402747392","peak_vmem":"2905161728","rchar":"32197873","wchar":"1288928","syscr":"6303","syscw":"1485","read_bytes":"60127232","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/ef\/14c39442d7fb3abaaedb41efff3d24","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n### Random insertion sites\\n\\n\" > report.rmd\n    random_insertion.R \"test.fastq2_annot.pos\" \"motif_sites.pos\" \"2320711 2320942\" \"4627368 4627400\" \"G[AT]T\" \"4641652\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"random_insertion_report.txt\" \"report.rmd\"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n#### Insertion site counts\\n\\n\" > report.rmd\n    echo -e \'\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 14: Number of motifs insertion per fork](.\/figures\/plot_motif_insertion_per_fork.png){width=400}\n\\n\\n<\/center>\\n\\n\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 15: Number of motifs insertion per strand](.\/figures\/plot_motif_insertion_per_strand.png){width=400}\n\\n\\n<\/center>\\n\\n\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 16: Number of motifs insertion per strand](.\/figures\/plot_motif_insertion_per_strand.png){width=400}\n\\n\\n<\/center>\\n\\n\n    \' >> report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n#### Insertion site proportions\\n\\n\" >> report.rmd\n    echo -e \'\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 17: Proportion of motifs insertion per fork](.\/figures\/plot_motif_insertion_per_fork_prop.png){width=500}\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 18: Proportion of motifs insertion per strand](.\/figures\/plot_motif_insertion_per_strand_prop.png){width=500}\n\\n\\n<\/center>\\n\\n\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 19: Proportion of motifs insertion per strand](.\/figures\/plot_motif_insertion_per_fork_and_strand_prop.png){width=500}\n\\n\\n<\/center>\\n\\n\n    \' >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"62044","inv_ctxt":"83"},{"task_id":"39","hash":"cb\/a45b2e","native_id":"21670","process":"report2","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"report2","status":"COMPLETED","exit":"0","submit":"1645559068329","start":"1645559068413","complete":"1645559069796","duration":"1467","realtime":"26","%cpu":"8.5","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"133952","wchar":"1289","syscr":"245","syscw":"88","read_bytes":"242688","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/cb\/a45b2e53c4362caaa6669c72ad8f93","script":"\n    echo -e \"\n\\n\\n<br \/><br \/>\\n\\n###  Logos\\n\\n\n\\n\\nIn each sequence of length $((20 * 2)) <br \/>position $((20 + 1)) corresponds to the first nucleotide of the reference genome part of the read\n\" > report.rmd\n    count=0\n    for i in $(echo [test.fastq2_LEADING_0, test.fastq2_LAGGING_16, test.fastq2_LAGGING_0, test.fastq2_LEADING_16] | sed \'s\/^\\[\/\/\' | sed \'s\/\\]$\/\/\' | sed \'s\/,\/\/g\') ; do\n        echo -e \'\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure \'$((9 + $count))\': \'${i}\'](.\/figures\/logo_\'${i}\'.png){width=600}\n\\n\\n<\/center>\\n\\n\n        \' >> report.rmd\n        count=$((count + 1))\n    done\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645559065\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"37","hash":"cb\/7fbfc4","native_id":"17176","process":"logo","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"logo (1)","status":"CACHED","exit":"0","submit":"1645558941604","start":"1645558941697","complete":"1645558951176","duration":"9572","realtime":"8824","%cpu":"61.0","%mem":"0.2","rss":"211927040","vmem":"2581889024","peak_rss":"211927040","peak_vmem":"2582429696","rchar":"15274134","wchar":"894677","syscr":"2841","syscw":"319","read_bytes":"55312384","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/cb\/7fbfc4a56467231071b31d5fafc1d0","script":"\n    logo.R \"test.fastq2_LAGGING_0.stat\" 20 \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"logo_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"53022","inv_ctxt":"6"},{"task_id":"40","hash":"53\/74fd55","native_id":"19631","process":"global_logo","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"global_logo","status":"CACHED","exit":"0","submit":"1645558980113","start":"1645558980207","complete":"1645558989787","duration":"9674","realtime":"8967","%cpu":"63.6","%mem":"0.2","rss":"213176320","vmem":"2580549632","peak_rss":"213176320","peak_vmem":"2581069824","rchar":"15282864","wchar":"870727","syscr":"2850","syscw":"333","read_bytes":"55312384","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/53\/74fd55808d8c6c5e6a89a46bf03baa","script":"\n    global_logo.R \"test.fastq2_LAGGING_0.stat test.fastq2_LEADING_16.stat test.fastq2_LAGGING_16.stat test.fastq2_LEADING_0.stat\" test.fastq2 20 \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"global_logo_report.txt\"\n    echo -e \'\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 13: test.fastq2 global logo](.\/figures\/global_logo_test.fastq2.png){width=600}\n\\n\\n<\/center>\\n\\n\n    \' >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"53159","inv_ctxt":"4"},{"task_id":"36","hash":"f6\/b96d60","native_id":"18408","process":"logo","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"logo (3)","status":"CACHED","exit":"0","submit":"1645558960654","start":"1645558960747","complete":"1645558970226","duration":"9572","realtime":"8876","%cpu":"61.1","%mem":"0.2","rss":"213983232","vmem":"2581954560","peak_rss":"213983232","peak_vmem":"2582523904","rchar":"15274126","wchar":"903827","syscr":"2839","syscw":"321","read_bytes":"55312384","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/f6\/b96d608d69d0c41707b7541fbf50f9","script":"\n    logo.R \"test.fastq2_LAGGING_16.stat\" 20 \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"logo_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"53020","inv_ctxt":"4"},{"task_id":"35","hash":"54\/42a221","native_id":"19019","process":"logo","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"logo (4)","status":"CACHED","exit":"0","submit":"1645558970233","start":"1645558970326","complete":"1645558980106","duration":"9873","realtime":"9163","%cpu":"59.9","%mem":"0.2","rss":"216498176","vmem":"2584637440","peak_rss":"216498176","peak_vmem":"2585157632","rchar":"15274102","wchar":"1026301","syscr":"2845","syscw":"337","read_bytes":"55312384","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/54\/42a221f2ccf7068389597b30193203","script":"\n    logo.R \"test.fastq2_LEADING_0.stat\" 20 \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"logo_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"52914","inv_ctxt":"7"},{"task_id":"38","hash":"13\/c75c72","native_id":"17797","process":"logo","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"logo (2)","status":"CACHED","exit":"0","submit":"1645558951183","start":"1645558951276","complete":"1645558960647","duration":"9464","realtime":"8756","%cpu":"61.4","%mem":"0.2","rss":"240406528","vmem":"2581323776","peak_rss":"240406528","peak_vmem":"2581856256","rchar":"15274075","wchar":"873353","syscr":"2837","syscw":"320","read_bytes":"55312384","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/13\/c75c72ebe6b5033aecdee638e2fcb3","script":"\n    logo.R \"test.fastq2_LEADING_16.stat\" 20 \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"logo_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"53087","inv_ctxt":"12"},{"task_id":"41","hash":"b7\/0ba328","native_id":"20250","process":"plot_insertion","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"plot_insertion (1)","status":"CACHED","exit":"0","submit":"1645558989794","start":"1645558989887","complete":"1645559026467","duration":"36673","realtime":"36002","%cpu":"74.6","%mem":"1.0","rss":"1047265280","vmem":"3413561344","peak_rss":"1047265280","peak_vmem":"3413585920","rchar":"42236034","wchar":"10194994","syscr":"11025","syscw":"1835","read_bytes":"74364928","write_bytes":"24576","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/b7\/0ba328f850a5bf8d897084806adfad","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Insertion plots\\n\\n\" > report.rmd\n    plot_insertion.R \"obs_rd_insertions.pos\" \"obs_rd_insertions.freq\" \"2320711 2320942\" \"4627368 4627400\" \"Ecoli Genome (bp)\" \"4641652\" \"50000\" \"100\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"plot_insertion_report.txt\"\n    echo -e \"\\n\\n####  Histograms\\n\\n\" >> report.rmd\n    echo -e \'\n\\n\\n<\/center>\\n\\n\n![Figure 20: Insertion site usage (total insertions).](.\/figures\/plot_test.fastq2_insertion_hist_tot.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n\n![Figure 21: Insertion site usage zoomed for sites with few insertions (total insertions).](.\/figures\/plot_test.fastq2_insertion_hist_tot_zoom.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n\n![Figure 22: Insertion site usage (forward strand).](.\/figures\/plot_test.fastq2_insertion_hist_forward.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n\n![Figure 23: Insertion site usage (reverse strand).](.\/figures\/plot_test.fastq2_insertion_hist_reverse.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n\n    \' >> report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n####  Raw frequencies\\n\\n\" >> report.rmd\n    echo -e \"\\n\\nSee the CL Labbook section 24.7.3 to explain the limitation around 100 bp\\n\" >> report.rmd\n    echo -e \'\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n\n![Figure 24: Raw insertion frequencies.](.\/figures\/plot_test.fastq2_insertion_raw.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n\n    \' >> report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n####  Binned frequencies\\n\\n\" >> report.rmd\n    count=1\n    for i in 50000 ; do\n        echo -e \'\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure \'$((24 + $count))\': frequencies using the binning range of \'$(printf \"%\'d\" ${i})\'](.\/figures\/plot_test.fastq2_insertion_bin_\'${i}\'.png){width=600}\n\\n\\n<\/center>\\n\\n\n        \' >> report.rmd\n        count=$((count + 1))\n        echo -e \'\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure \'$((24 + $count))\': frequencies using the binning range of \'$(printf \"%\'d\" ${i})\'](.\/figures\/plot_test.fastq2_lead_lag_insertion_bin_\'${i}\'.png){width=600}\n\\n\\n<\/center>\\n\\n\n        \' >> report.rmd\n        count=$((count + 1))\n    done\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_res_CL14985_B4985_4_1645558839\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"73352","inv_ctxt":"20"},{"task_id":"42","hash":"41\/e917b4","native_id":"22159","process":"print_report","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"print_report (1)","status":"COMPLETED","exit":"0","submit":"1645559070332","start":"1645559070367","complete":"1645559080807","duration":"10475","realtime":"9707","%cpu":"54.9","%mem":"0.3","rss":"255709184","vmem":"1102452711424","peak_rss":"255709184","peak_vmem":"1102518931456","rchar":"32733838","wchar":"12168741","syscr":"5146","syscw":"1052","read_bytes":"54798336","write_bytes":"4096","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/41\/e917b4bc1a6a96c455c1bbe84b9d14","script":"\n    cp report.rmd report_file.rmd # this is to get hard files, not symlinks\n    mkdir figures\n    mkdir files\n    mkdir reports\n    cat stat_tempo > .\/files\/test.fastq2_5pAttc_1-51.stat # this is to get hard files, not symlinks\n    cp head.fw.txt head.rv.txt table1.txt table2.txt table3.txt table4.txt table8.txt .\/files\/ # this is to get hard files, not symlinks\n    cp plot_fivep_filtering_stat.png plot_read_length_cutoff.png plot_read_length_fivep_filtering.png plot_read_length_fivep_filtering_cut.png plot_read_length_ini.png plot_test.fastq2_bowtie2_mini.png plot_test.fastq2_q20_mini.png plot_test.fastq2_q20_nodup_mini.png logo_test.fastq2_LAGGING_0.png logo_test.fastq2_LAGGING_16.png logo_test.fastq2_LEADING_0.png logo_test.fastq2_LEADING_16.png global_logo_test.fastq2.png plot_motif_insertion_per_fork.png plot_motif_insertion_per_fork_and_strand.png plot_motif_insertion_per_fork_and_strand_prop.png plot_motif_insertion_per_fork_prop.png plot_motif_insertion_per_strand.png plot_motif_insertion_per_strand_prop.png plot_test.fastq2_insertion_bin_50000.png plot_test.fastq2_insertion_hist_forward.png plot_test.fastq2_insertion_hist_reverse.png plot_test.fastq2_insertion_hist_tot.png plot_test.fastq2_insertion_hist_tot_zoom.png plot_test.fastq2_insertion_raw.png plot_test.fastq2_lead_lag_insertion_bin_50000.png .\/figures\/ # Warning several files\n    cp plot_fivep_filtering_stat.png .\/reports\/nf_dag.png # trick to delude the knitting during the print report\n    cp multiqc_report.html .\/reports\/ # this is to get hard files, not symlinks\n    print_report.R \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"report_file.rmd\" \"print_report.txt\"\n    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workflowVersion","q3Label":"workflowVersion"},"time":{"mean":637,"min":637,"q1":637,"q2":637,"q3":637,"max":637,"minLabel":"workflowVersion","maxLabel":"workflowVersion","q1Label":"workflowVersion","q2Label":"workflowVersion","q3Label":"workflowVersion"},"writes":{"mean":1712,"min":1712,"q1":1712,"q2":1712,"q3":1712,"max":1712,"minLabel":"workflowVersion","maxLabel":"workflowVersion","q1Label":"workflowVersion","q2Label":"workflowVersion","q3Label":"workflowVersion"}},{"cpuUsage":{"mean":54.9,"min":54.9,"q1":54.9,"q2":54.9,"q3":54.9,"max":54.9,"minLabel":"print_report (1)","maxLabel":"print_report (1)","q1Label":"print_report (1)","q2Label":"print_report (1)","q3Label":"print_report (1)"},"process":"print_report","mem":{"mean":255709184,"min":255709184,"q1":255709184,"q2":255709184,"q3":255709184,"max":255709184,"minLabel":"print_report (1)","maxLabel":"print_report (1)","q1Label":"print_report (1)","q2Label":"print_report (1)","q3Label":"print_report (1)"},"memUsage":{"mean":0.37,"min":0.37,"q1":0.37,"q2":0.37,"q3":0.37,"max":0.37,"minLabel":"print_report (1)","maxLabel":"print_report (1)","q1Label":"print_report (1)","q2Label":"print_report (1)","q3Label":"print_report (1)"},"timeUsage":null,"vmem":{"mean":1102518931456,"min":1102518931456,"q1":1102518931456,"q2":1102518931456,"q3":1102518931456,"max":1102518931456,"minLabel":"print_report (1)","maxLabel":"print_report (1)","q1Label":"print_report (1)","q2Label":"print_report (1)","q3Label":"print_report (1)"},"reads":{"mean":32733838,"min":32733838,"q1":32733838,"q2":32733838,"q3":32733838,"max":32733838,"minLabel":"print_report (1)","maxLabel":"print_report (1)","q1Label":"print_report (1)","q2Label":"print_report (1)","q3Label":"print_report (1)"},"cpu":{"mean":54.9,"min":54.9,"q1":54.9,"q2":54.9,"q3":54.9,"max":54.9,"minLabel":"print_report (1)","maxLabel":"print_report (1)","q1Label":"print_report (1)","q2Label":"print_report (1)","q3Label":"print_report (1)"},"time":{"mean":9707,"min":9707,"q1":9707,"q2":9707,"q3":9707,"max":9707,"minLabel":"print_report (1)","maxLabel":"print_report (1)","q1Label":"print_report (1)","q2Label":"print_report (1)","q3Label":"print_report (1)"},"writes":{"mean":12168741,"min":12168741,"q1":12168741,"q2":12168741,"q3":12168741,"max":12168741,"minLabel":"print_report (1)","maxLabel":"print_report (1)","q1Label":"print_report (1)","q2Label":"print_report (1)","q3Label":"print_report (1)"}}] };
+{"task_id":"5","hash":"6b\/c7fecc","native_id":"3736","process":"backup","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"backup","status":"COMPLETED","exit":"0","submit":"1645716348774","start":"1645716348848","complete":"1645716350250","duration":"1476","realtime":"13","%cpu":"5.5","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"106759","wchar":"500","syscr":"189","syscw":"23","read_bytes":"242688","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/6b\/c7fecc89abb52ecc8b628440668057","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Backup\\n\\n\" > report.rmd\n    echo -e \"See the [reports](.\/reports) folder for all the details of the analysis, including the parameters used in the .config file\" >> report.rmd\n    echo -e \"\\n\\nFull .nextflow.log is in: \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot<br \/>The one in the [reports](.\/reports) folder is not complete (miss the end)\" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"2","hash":"0a\/e411b8","native_id":"3764","process":"Nremove","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"Nremove (1)","status":"COMPLETED","exit":"0","submit":"1645716348799","start":"1645716348863","complete":"1645716350697","duration":"1898","realtime":"435","%cpu":"45.9","%mem":"0.0","rss":"12656640","vmem":"73986048","peak_rss":"12656640","peak_vmem":"73998336","rchar":"17604810","wchar":"15167117","syscr":"1863","syscw":"1271","read_bytes":"568320","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/0a\/e411b8f53190b555df28ff3c9ad900","script":"\n    Nremove.sh test.fastq2.gz \"test.fastq2_Nremove.gz\" \"report.rmd\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"901","inv_ctxt":"3"},{"task_id":"1","hash":"bf\/506112","native_id":"3796","process":"init","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"init","status":"COMPLETED","exit":"0","submit":"1645716348822","start":"1645716348876","complete":"1645716350408","duration":"1586","realtime":"11","%cpu":"5.3","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"106557","wchar":"665","syscr":"190","syscw":"26","read_bytes":"242688","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/bf\/506112e1cf202cedfd3307e8a24513","script":"\n    echo \"---\n    title: \'Insertion Sites Report\'\n    author: \'Gael Millot\'\n    date: \'`r Sys.Date()`\'\n    output:\n      html_document:\n        toc: TRUE\n        toc_float: TRUE\n    ---\n\n    \\n\\n<br \/><br \/>\\n\\n\n    \" > report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"3","hash":"4b\/1f154d","native_id":"3854","process":"report1","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"report1","status":"COMPLETED","exit":"0","submit":"1645716348846","start":"1645716348890","complete":"1645716350548","duration":"1702","realtime":"20","%cpu":"4.9","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"106922","wchar":"679","syscr":"189","syscw":"54","read_bytes":"242688","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/4b\/1f154d3495c00bcfbd4b578785097f","script":"\n    echo -e \'\n\\n\\n<br \/><br \/>\\n\\n###  Read coverage\\n\\n\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 6: After Bowtie2 alignment](.\/figures\/plot_test.fastq2_bowtie2_mini.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 7: After Mapping Quality Q20 (1%) filtering](.\/figures\/plot_test.fastq2_q20_mini.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 8: After removal of reads with identical 5\' and 3\' coordinates](.\/figures\/plot_test.fastq2_q20_nodup_mini.png){width=600}\n\\n\\n<\/center>\\n\\n\n    \' > report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"6","hash":"03\/f78123","native_id":"3906","process":"workflowVersion","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"workflowVersion","status":"COMPLETED","exit":"0","submit":"1645716348869","start":"1645716348948","complete":"1645716351088","duration":"2219","realtime":"711","%cpu":"11.8","%mem":"0.0","rss":"5087232","vmem":"40304640","peak_rss":"5087232","peak_vmem":"40304640","rchar":"136509","wchar":"2131","syscr":"301","syscw":"67","read_bytes":"1481728","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/03\/f781239882e1c3237d15e01a47a3f1","script":"\n    modules= # this is just to deal with variable interpretation during the creation of the .command.sh file by nextflow. See also $modules below\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Workflow Version\\n\\n\" > report.rmd\n    echo -e \"\\n\\n#### GENERAL\\n\\n\n| Variable | Value |\n| :-- | :-- |\n| Project<br \/>(empty means no .git folder where the main.nf file is present) | $(git -C \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot remote -v | head -n 1) | # works only if the main script run is located in a directory that has a .git folder, i.e., that is connected to a distant repo\n| Git info<br \/>(empty means no .git folder where the main.nf file is present) | $(git -C \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot describe --abbrev=10 --dirty --always --tags) | # idem. Provide the small commit number of the script and nextflow.config used in the execution\n| Cmd line | nextflow run main.nf -resume |\n| execution mode | local |\" >> report.rmd \n\n    if [[ ! -z $modules ]] ; then\n        echo \"| loaded modules (according to specification by the user thanks to the --modules argument of main.nf) |  |\" >> report.rmd\n    fi\n    \n    echo \"| Manifest\'s pipeline version | null |\n| result path | \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342 |\n| nextflow version | 21.04.2 |\n    \" >> report.rmd\n\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n#### IMPLICIT VARIABLES\\n\\n\n| Name | Description | Value | \n| :-- | :-- | :-- |\n| launchDir | Directory where the workflow is run | \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot |\n| nprojectDir | Directory where the main.nf script is located | \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot |\n| workDir | Directory where tasks temporary files are created | \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work |\n    \" >> report.rmd\n\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n#### USER VARIABLES\\n\\n\n| Name | Description | Value | \n| :-- | :-- | :-- |\n| out_path | output folder path | \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342 |\n| in_path | input folder path | \/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset |\n    \" >> report.rmd\n\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n#### WORKFLOW DIAGRAM\\n\\nSee the [nf_dag.png](.\/reports\/nf_dag.png) file\" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"29","inv_ctxt":"1"},{"task_id":"7","hash":"31\/65ff8a","native_id":"4579","process":"trim","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-alien_trimmer_v0.4.0-gitlab_v8.1.img","tag":"-","name":"trim (1)","status":"COMPLETED","exit":"0","submit":"1645716358514","start":"1645716358599","complete":"1645716361558","duration":"3044","realtime":"2110","%cpu":"44.2","%mem":"0.0","rss":"40587264","vmem":"5903626240","peak_rss":"40587264","peak_vmem":"5970448384","rchar":"17145212","wchar":"12629480","syscr":"2381","syscw":"647","read_bytes":"9977856","write_bytes":"32768","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/31\/65ff8abf7d1c75c59972a23fc8e361","script":"\n    trim.sh test.fastq2_Nremove.gz \"test.fastq2_trim.fq\" 20200520_adapters_TruSeq_B2699_14985_CL.fasta 30 \"report.rmd\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"3267","inv_ctxt":"0"},{"task_id":"10","hash":"b2\/dfc998","native_id":"4993","process":"kraken","module":"-","container":"-","tag":"-","name":"kraken (1)","status":"COMPLETED","exit":"0","submit":"1645716361603","start":"1645716361657","complete":"1645716361692","duration":"89","realtime":"9","%cpu":"41.0","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"154433","wchar":"220","syscr":"228","syscw":"13","read_bytes":"159744","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/b2\/dfc998bc44eebc8510857af74ed894","script":"\n        echo \"No kraken analysis performed in local running\" > test.fastq2_trim_kraken_std.txt\n        ","scratch":"-","queue":"-","cpus":"1","memory":"-","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"9","hash":"fa\/c1fd48","native_id":"5007","process":"fivep_filtering","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"fivep_filtering (1)","status":"COMPLETED","exit":"0","submit":"1645716361621","start":"1645716361668","complete":"1645716364528","duration":"2907","realtime":"1958","%cpu":"21.5","%mem":"0.0","rss":"10018816","vmem":"64376832","peak_rss":"10018816","peak_vmem":"64376832","rchar":"29336512","wchar":"16062033","syscr":"9150","syscw":"5787","read_bytes":"437248","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/fa\/c1fd482e7170ed345cdc16d1c9ab66","script":"\n    fivep_filtering.sh test.fastq2_trim.fq \"test.fastq2\" \"^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\" 48 3 51 \"CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\" \"report.rmd\"\n    echo \"Nucleotide frequencies of the 5\' part of reads:\n\n\" >> report.rmd\n    echo \"\n\\`\\`\\`{r, echo = FALSE}\ntempo <- read.table(\'.\/files\/test.fastq2_5pAttc_1-51.stat\', header = TRUE, row.names = 1, colClasses = \'character\', sep = \'\\t\', check.names = FALSE) ; \nkableExtra::kable_styling(knitr::kable(head(tempo), row.names = TRUE, digits = 2, caption = NULL, format=\'html\'), c(\'striped\', \'bordered\', \'responsive\', \'condensed\'), font_size=10, full_width = FALSE, position = \'left\')\n\\`\\`\\`\n    \n\n\n    \" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"8220","inv_ctxt":"0"},{"task_id":"11","hash":"c9\/fb815c","native_id":"5361","process":"cutoff","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"cutoff (1)","status":"COMPLETED","exit":"0","submit":"1645716364576","start":"1645716364629","complete":"1645716366378","duration":"1802","realtime":"740","%cpu":"15.7","%mem":"0.0","rss":"10166272","vmem":"64229376","peak_rss":"10166272","peak_vmem":"64229376","rchar":"7308005","wchar":"4049154","syscr":"2784","syscw":"2034","read_bytes":"384000","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/c9\/fb815cd30f073585191458f206dfce","script":"\n    cutoff.sh test.fastq2_5pAtccRm.fq 25 \"test.fastq2\" \"report.rmd\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"1185","inv_ctxt":"0"},{"task_id":"8","hash":"dc\/1c3599","native_id":"5579","process":"fastqc1","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/evolbioinfo-fastqc-v0.11.8.img","tag":"-","name":"fastqc1 (1)","status":"COMPLETED","exit":"0","submit":"1645716369105","start":"1645716369181","complete":"1645716376788","duration":"7683","realtime":"6609","%cpu":"50.3","%mem":"0.2","rss":"167321600","vmem":"3289468928","peak_rss":"167321600","peak_vmem":"3289890816","rchar":"14603837","wchar":"1278925","syscr":"7605","syscw":"5170","read_bytes":"19984384","write_bytes":"712704","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/dc\/1c3599d32674f4e310ebcf6e9778ea","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Read QC n\u00B01\\n\\n\" > report.rmd\n    echo -e \"Results are published in the [fastQC1](.\/fastQC1) folder\\n\\n\" >> report.rmd\n    fastqc test.fastq2_trim.fq | tee tempo.txt\n    cat tempo.txt >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"-","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"4344","inv_ctxt":"0"},{"task_id":"12","hash":"16\/720a57","native_id":"5600","process":"fastqc2","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/evolbioinfo-fastqc-v0.11.8.img","tag":"-","name":"fastqc2 (1)","status":"COMPLETED","exit":"0","submit":"1645716369125","start":"1645716369205","complete":"1645716376867","duration":"7742","realtime":"6628","%cpu":"48.5","%mem":"0.1","rss":"157093888","vmem":"3289468928","peak_rss":"157093888","peak_vmem":"3342655488","rchar":"12766798","wchar":"1245411","syscr":"7360","syscw":"5096","read_bytes":"19984384","write_bytes":"688128","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/16\/720a57cb9b917c09ee8a57661ad65c","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Read QC n\u00B02\\n\\n\" > report.rmd\n    echo -e \"Results are published in the [fastQC2](.\/fastQC2) folder\\n\\n\" >> report.rmd\n    fastqc test.fastq2_5pAtccRm.fq | tee tempo.txt\n    cat tempo.txt >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"-","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"4344","inv_ctxt":"2"},{"task_id":"14","hash":"ea\/2dce38","native_id":"6271","process":"bowtie2","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bowtie2_v2.3.4.3_extended_v2.0-gitlab_v8.0.img","tag":"-","name":"bowtie2 (1)","status":"COMPLETED","exit":"0","submit":"1645716372936","start":"1645716372987","complete":"1645716377778","duration":"4842","realtime":"3683","%cpu":"51.4","%mem":"0.0","rss":"66875392","vmem":"249085952","peak_rss":"120135680","peak_vmem":"251146240","rchar":"36678359","wchar":"17009937","syscr":"3393","syscw":"2520","read_bytes":"7209984","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/ea\/2dce38b9fc4a9628a96e45160a9448","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Bowtie2 indexing of the reference sequence\\n\\n\" >> bowtie2_report.txt\n    bowtie2-build Ecoli-K12-MG1655_ORI_CENTERED.fasta Ecoli-K12-MG1655_ORI_CENTERED |& tee -a bowtie2_report.txt\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Bowtie2 alignment\\n\\n\" > report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Bowtie2 alignment\\n\\n\" >> bowtie2_report.txt\n    bowtie2 --very-sensitive -x Ecoli-K12-MG1655_ORI_CENTERED -U test.fastq2_cutoff.fq -t -S test.fastq2_bowtie2.sam |& tee -a tempo.txt\n    # --very-sensitive: no soft clipping allowed and very sensitive seed alignment\n    # -t time displayed\n    cat tempo.txt >> bowtie2_report.txt\n    sed -i -e \':a;N;$!ba;s\/\\n\/\\n<br \\\/>\/g\' tempo.txt\n    cat tempo.txt >> report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n####  samtools conversion\\n\\n\" >> bowtie2_report.txt\n    # samtools faidx Ecoli-K12-MG1655_ORI_CENTERED.fasta\n    samtools view -bh -o tempo.bam test.fastq2_bowtie2.sam |& tee -a bowtie2_report.txt\n    samtools sort -o test.fastq2_bowtie2.bam tempo.bam |& tee -a bowtie2_report.txt\n    samtools index test.fastq2_bowtie2.bam |& tee -a bowtie2_report.txt\n    ","scratch":"-","queue":"-","cpus":"12","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"5851","inv_ctxt":"36"},{"task_id":"18","hash":"93\/1153d4","native_id":"7377","process":"multiQC","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/ewels-multiqc-1.10.1.img","tag":"-","name":"multiQC","status":"COMPLETED","exit":"0","submit":"1645716383461","start":"1645716383484","complete":"1645716392498","duration":"9037","realtime":"9000","%cpu":"37.1","%mem":"0.1","rss":"78508032","vmem":"89317376","peak_rss":"78708736","peak_vmem":"89489408","rchar":"29684849","wchar":"2404815","syscr":"9285","syscw":"289","read_bytes":"22820864","write_bytes":"1253376","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/93\/1153d4999b615ba1588b10ad731538","script":"\n    multiqc . -n multiqc_report.html\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  MultiQC\\n\\n\" > report.rmd\n    echo -e \"Results are published in the [Report](.\/reports\/multiqc_report.html) folder\\n\\n\" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"-","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"35805","inv_ctxt":"44"},{"task_id":"16","hash":"09\/3abd99","native_id":"7440","process":"Q20","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-samtools_v1.14-gitlab_v8.0.img","tag":"-","name":"Q20 (1)","status":"COMPLETED","exit":"0","submit":"1645716383680","start":"1645716383684","complete":"1645716385238","duration":"1558","realtime":"415","%cpu":"16.5","%mem":"0.0","rss":"6111232","vmem":"44822528","peak_rss":"6111232","peak_vmem":"44830720","rchar":"3392005","wchar":"2260606","syscr":"889","syscw":"567","read_bytes":"1229824","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/09\/3abd994fee0cb2d4325a541fd7d8ce","script":"\n    samtools view -q 20 -b test.fastq2_bowtie2.bam > test.fastq2_q20.bam |& tee q20_report.txt\n    samtools index test.fastq2_q20.bam\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Q20 filtering\\n\\n\" > report.rmd\n    read_nb_before=$(samtools view test.fastq2_bowtie2.bam | wc -l | cut -f1 -d\' \') # -h to add the header\n    read_nb_after=$(samtools view test.fastq2_q20.bam | wc -l | cut -f1 -d\' \') # -h to add the header\n    echo -e \"\\n\\nNumber of sequences before Q20 filtering: $(printf \"%\'d\" ${read_nb_before})\\n\" >> report.rmd\n    echo -e \"\\n\\nNumber of sequences after Q20 filtering: $(printf \"%\'d\" ${read_nb_after})\\n\" >> report.rmd\n    echo -e \"Ratio: \" >> report.rmd\n    echo -e $(printf \"%.2f\n\" $(echo $\" $read_nb_after \/ $read_nb_before \" | bc -l)) >> report.rmd # the number in \'%.2f\\n\' is the number of decimals\n    echo -e \"\\n\\n\" >> report.rmd\n    echo $read_nb_before > read_nb_before # because nf cannot output values easily\n    echo $read_nb_after > read_nb_after\n    ","scratch":"-","queue":"-","cpus":"1","memory":"1073741824","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"811","inv_ctxt":"0"},{"task_id":"17","hash":"44\/53399e","native_id":"7603","process":"coverage","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bedtools_v2.30.0-gitlab_v8.0.img","tag":"-","name":"coverage (1)","status":"COMPLETED","exit":"0","submit":"1645716384875","start":"1645716384885","complete":"1645716386798","duration":"1923","realtime":"885","%cpu":"15.7","%mem":"0.0","rss":"5210112","vmem":"46727168","peak_rss":"5210112","peak_vmem":"46727168","rchar":"491158","wchar":"93146","syscr":"251","syscw":"3116","read_bytes":"1734656","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/44\/53399e51aafb31a04837099720403d","script":"\n    # bedtools genomecov -d -ibam ${bam} > ${bam.baseName}.cov |& tee cov_report.txt # coverage per base if ever required but long process\n    # to add the chr names | awk \'{h[$NF]++}; END { for(k in h) print k, h[k] }\' | sort -V > ${bam.baseName}.cov\n    bedtools genomecov -bga -ibam test.fastq2_bowtie2.bam  > test.fastq2_bowtie2_mini.cov |& tee cov_report.txt\n    # -g ${ref} not required when inputs are bam files\n    ","scratch":"-","queue":"-","cpus":"12","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"640","inv_ctxt":"0"},{"task_id":"21","hash":"cd\/ab90a7","native_id":"7933","process":"no_soft_clipping","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-samtools_v1.14-gitlab_v8.0.img","tag":"-","name":"no_soft_clipping (1)","status":"COMPLETED","exit":"0","submit":"1645716386298","start":"1645716386340","complete":"1645716387937","duration":"1639","realtime":"340","%cpu":"10.8","%mem":"0.0","rss":"5578752","vmem":"60444672","peak_rss":"5578752","peak_vmem":"60444672","rchar":"2188546","wchar":"1583809","syscr":"702","syscw":"417","read_bytes":"1153024","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/cd\/ab90a7838af23e877e5e762da60a9e","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Control that no more soft clipping in reads\\n\\n\" > report.rmd\n    echo -e \"nb of reads with soft clipping (S) in CIGAR: $(printf \"%\'d\" $(samtools view test.fastq2_q20.bam | awk \'$6 ~ \/.*[S].*\/{print $0}\' | wc -l | cut -f1 -d\' \'))\" >> report.rmd\n    echo -e \"\\n\\ntotal nb of reads: $(printf \"%\'d\" $(samtools view test.fastq2_q20.bam | wc -l | cut -f1 -d\' \'))\" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"1073741824","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"31","inv_ctxt":"11"},{"task_id":"20","hash":"c1\/88ba17","native_id":"7953","process":"duplicate_removal","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-samtools_v1.14-gitlab_v8.0.img","tag":"-","name":"duplicate_removal (1)","status":"COMPLETED","exit":"0","submit":"1645716386318","start":"1645716386352","complete":"1645716389847","duration":"3529","realtime":"2207","%cpu":"23.3","%mem":"0.0","rss":"7925760","vmem":"55619584","peak_rss":"7925760","peak_vmem":"55619584","rchar":"13491554","wchar":"6912400","syscr":"7204","syscw":"5709","read_bytes":"1376256","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/c1\/88ba173ae6c0c507a0a2ec13e80992","script":"\n    duplicate_removal.sh test.fastq2_q20.bam Ecoli-K12-MG1655_ORI_CENTERED.fasta \"test.fastq2_q20_nodup.bam\" \"dup_report.txt\" \"report.rmd\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"1073741824","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"1877","inv_ctxt":"3"},{"task_id":"19","hash":"36\/3097aa","native_id":"8065","process":"coverage","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bedtools_v2.30.0-gitlab_v8.0.img","tag":"-","name":"coverage (2)","status":"COMPLETED","exit":"0","submit":"1645716386840","start":"1645716386898","complete":"1645716389018","duration":"2178","realtime":"913","%cpu":"13.8","%mem":"0.0","rss":"5287936","vmem":"46522368","peak_rss":"5287936","peak_vmem":"46538752","rchar":"343026","wchar":"84345","syscr":"239","syscw":"2824","read_bytes":"1734656","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/36\/3097aa0022fe90fe351bbae7862f46","script":"\n    # bedtools genomecov -d -ibam ${bam} > ${bam.baseName}.cov |& tee cov_report.txt # coverage per base if ever required but long process\n    # to add the chr names | awk \'{h[$NF]++}; END { for(k in h) print k, h[k] }\' | sort -V > ${bam.baseName}.cov\n    bedtools genomecov -bga -ibam test.fastq2_q20.bam  > test.fastq2_q20_mini.cov |& tee cov_report.txt\n    # -g ${ref} not required when inputs are bam files\n    ","scratch":"-","queue":"-","cpus":"12","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"600","inv_ctxt":"2"},{"task_id":"24","hash":"19\/def24f","native_id":"8911","process":"insertion","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-samtools_v1.14-gitlab_v8.0.img","tag":"-","name":"insertion (1)","status":"COMPLETED","exit":"0","submit":"1645716389880","start":"1645716389948","complete":"1645716391698","duration":"1818","realtime":"609","%cpu":"17.5","%mem":"0.0","rss":"9392128","vmem":"68771840","peak_rss":"9392128","peak_vmem":"68780032","rchar":"2612524","wchar":"1832054","syscr":"1555","syscw":"1165","read_bytes":"1238016","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/19\/def24f728f89d1c12aca6f40c66369","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n### Insertion positions\\n\\n\" > report.rmd\n    echo -e \"\\n\\nOne of the step is to correct insertion site read extremity for the reverse reads. It consist in the redefinition of POS according to FLAG in the bam file. See the [insertion_report.txt](.\/reports\/insertion_report.txt) file in the reports folders for details\\n\\n\" >> report.rmd\n    # extraction of bam column 2, 4 and 10, i.e., FALG, POS and SEQ\n    samtools view test.fastq2_q20_nodup.bam | awk \'BEGIN{FS=\"\\t\" ; OFS=\"\" ; ORS=\"\"}{print \">\"$2\"\\t\"$4\"\\n\"$10\"\\n\" }\' > tempo\n    # Of note, samtools fasta $DIR\/$SAMPLE_NAME > ${OUTPUT}.fasta # convert bam into fasta\n    echo -e \"\\n\\nExtraction of the FLAG (containing the read orientation) the POS and the SEQ of the bams\\nHeader is the 1) sens of insersion (0 or 16) and 2) insertion site position\\n\\n\" >> insertion_report.txt\n    cat tempo | head -60 | tail -20 >> insertion_report.txt\n    # redefinition of POS according to FLAG\n    awk \'BEGIN{FS=\"\t\" ; OFS=\"\" ; ORS=\"\"}{lineKind=(NR-1)%2}lineKind==0{orient=($1~\">16\") ; if(orient){var1 = $1 ; var2 = $2}else{print $0\"\\n\"}}lineKind==1{if(orient){var3 = length($0) ; var4 = var2 + var3 - 1 ; print var1\"\\t\"var4\"\\n\"$0\"\\n\"}else{print $0\"\\n\"}}\' tempo > test.fastq2_reorient.fasta\n    echo -e \"\\n\\nFinal fasta file\\n\\n\" >> insertion_report.txt\n    cat test.fastq2_reorient.fasta | head -60 | tail -20 >> insertion_report.txt\n    awk \'{lineKind=(NR-1)%2}lineKind==0{gsub(\/>\/, \"\", $1) ; print $0}\' test.fastq2_reorient.fasta > test.fastq2.pos\n    echo -e \"\\n\\nFinal pos file\\n\\n\" >> insertion_report.txt\n    cat test.fastq2.pos | head -60 | tail -20 >> insertion_report.txt\n\n    read_nb_before=$(samtools view test.fastq2_q20_nodup.bam | wc -l | cut -f1 -d\' \') # -h to add the header. Thus do not put here\n    read_nb_after=$(wc -l test.fastq2.pos | cut -f1 -d\' \')\n    echo -e \"\\n\\nNumber of reads used for insertion computation: $(printf \"%\'d\" ${read_nb_before})\\n\" >> report.rmd\n    echo -e \"\\n\\nNumber of insertions: $(printf \"%\'d\" ${read_nb_after})\\n\" >> report.rmd\n    echo -e \"Ratio: \" >> report.rmd\n    echo -e $(printf \"%.2f\n\" $(echo $\" $read_nb_after \/ $read_nb_before \" | bc -l)) >> report.rmd # the number in \'%.2f\\n\' is the number of decimals\n    echo -e \"\\n\\n\" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"1073741824","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"954","inv_ctxt":"5"},{"task_id":"25","hash":"e4\/43c3da","native_id":"8932","process":"coverage","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bedtools_v2.30.0-gitlab_v8.0.img","tag":"-","name":"coverage (3)","status":"COMPLETED","exit":"0","submit":"1645716389899","start":"1645716389959","complete":"1645716391917","duration":"2018","realtime":"844","%cpu":"14.8","%mem":"0.0","rss":"5378048","vmem":"46727168","peak_rss":"5378048","peak_vmem":"46727168","rchar":"317644","wchar":"84029","syscr":"235","syscw":"2820","read_bytes":"1734656","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/e4\/43c3daebbb13968cd29b75012679de","script":"\n    # bedtools genomecov -d -ibam ${bam} > ${bam.baseName}.cov |& tee cov_report.txt # coverage per base if ever required but long process\n    # to add the chr names | awk \'{h[$NF]++}; END { for(k in h) print k, h[k] }\' | sort -V > ${bam.baseName}.cov\n    bedtools genomecov -bga -ibam test.fastq2_q20_nodup.bam  > test.fastq2_q20_nodup_mini.cov |& tee cov_report.txt\n    # -g ${ref} not required when inputs are bam files\n    ","scratch":"-","queue":"-","cpus":"12","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"638","inv_ctxt":"0"},{"task_id":"27","hash":"fa\/585809","native_id":"9449","process":"seq_around_insertion","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"seq_around_insertion (1)","status":"COMPLETED","exit":"0","submit":"1645716403767","start":"1645716403811","complete":"1645716410157","duration":"6390","realtime":"5648","%cpu":"70.2","%mem":"0.1","rss":"163962880","vmem":"2515849216","peak_rss":"163962880","peak_vmem":"2515873792","rchar":"18784458","wchar":"234915","syscr":"2762","syscw":"362","read_bytes":"32610304","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/fa\/5858092595430631e02b8d58efa3bd","script":"\n    seq_around_insertion.R \"test.fastq2.pos\" \"2320711 2320942\" \"4627368 4627400\" \"20\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"seq_around_insertion_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"31133","inv_ctxt":"2"},{"task_id":"4","hash":"64\/dc0f4b","native_id":"9899","process":"motif","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"motif","status":"COMPLETED","exit":"0","submit":"1645716410167","start":"1645716410257","complete":"1645716424798","duration":"14631","realtime":"13912","%cpu":"65.4","%mem":"0.2","rss":"228462592","vmem":"2580992000","peak_rss":"228462592","peak_vmem":"2581016576","rchar":"50653126","wchar":"41640350","syscr":"6186","syscw":"34240","read_bytes":"32752640","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/64\/dc0f4b44fc526b11bfb78866c88f8d","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n### Motif detection\\n\\n\" > report.rmd\n    echo -e \"\\n\\nThe forward motif is: G[AT]T\\n\\n\" >> report.rmd\n    echo -e \"\\n\\nThe reverse motif is: A[AT]C\\n\\n\" >> report.rmd\n    if [[ G[AT]T != \"NULL\" ]] ; then\n        cat Ecoli-K12-MG1655_ORI_CENTERED.fasta | sed \'1d\' | grep -Ebo \'G[AT]T\' > motif_fw.pos\n        cat Ecoli-K12-MG1655_ORI_CENTERED.fasta | sed \'1d\' | grep -Ebo \'A[AT]C\' > motif_rev.pos\n    else\n        cat Ecoli-K12-MG1655_ORI_CENTERED.fasta | sed \'1d\' | grep -Ebo \'[ACGT]\' > motif_fw.pos\n        cat Ecoli-K12-MG1655_ORI_CENTERED.fasta | sed \'1d\' | grep -Ebo \'[ACGT]\' > motif_rev.pos\n    fi\n    echo -e \"\nINDICATED POSITIONS IN FILES START AT ZERO AND CORRESPOND TO THE FIRST LEFT BASE OF THE MOTIF\n\"\n    motif.R \"motif_fw.pos\" \"motif_rev.pos\" \"2320711 2320942\" \"4627368 4627400\" \"4641652\" \"G[AT]T\" \"A[AT]C\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"motif_report.txt\" \"report.rmd\"\n\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"54202","inv_ctxt":"32"},{"task_id":"26","hash":"95\/7e25d2","native_id":"10621","process":"final_insertion_files","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"final_insertion_files (1)","status":"COMPLETED","exit":"0","submit":"1645716424805","start":"1645716424898","complete":"1645716431207","duration":"6402","realtime":"5647","%cpu":"70.8","%mem":"0.1","rss":"164904960","vmem":"2517241856","peak_rss":"164904960","peak_vmem":"2517266432","rchar":"18856193","wchar":"272414","syscr":"2800","syscw":"510","read_bytes":"32802816","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/95\/7e25d2205e4237c1ffa82814a07246","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Final insertion site files\\n\\n\" > report.rmd\n    echo -e \"\\n\\nSee the [test.fastq2_annot.pos](.\/files\/test.fastq2_annot.pos) and [test.fastq2_annot.freq](.\/files\/test.fastq2_annot.freq) files\\n\\n\" >> report.rmd\n    final_insertion_files.R \"test.fastq2.pos\" \"2320711 2320942\" \"4627368 4627400\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"final_insertion_files_report.txt\"\n    pos_nb=$(wc -l test.fastq2_annot.pos | cut -f1 -d\' \')\n    echo -e \"\\n\\nNumber of different positions: $(printf \"%\'d\" ${pos_nb})\\n\" >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"31539","inv_ctxt":"4"},{"task_id":"28","hash":"2c\/4408b4","native_id":"11081","process":"plot_coverage","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"plot_coverage (3)","status":"COMPLETED","exit":"0","submit":"1645716431216","start":"1645716431308","complete":"1645716445468","duration":"14252","realtime":"13574","%cpu":"64.6","%mem":"0.2","rss":"261353472","vmem":"2628349952","peak_rss":"261353472","peak_vmem":"2628403200","rchar":"20056289","wchar":"470111","syscr":"4353","syscw":"302","read_bytes":"74364928","write_bytes":"24576","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/2c\/4408b494e84c46a4e12c745b700514","script":"\n    plot_coverage.R \"test.fastq2_q20_nodup_mini\" \"dup_read_nb\" \"2320711 2320942\" \"4627368 4627400\" \"5\" \"Ecoli Genome (bp)\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"plot_coverage_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"52629","inv_ctxt":"7"},{"task_id":"22","hash":"ba\/641b5b","native_id":"11803","process":"plot_coverage","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"plot_coverage (1)","status":"COMPLETED","exit":"0","submit":"1645716445475","start":"1645716445568","complete":"1645716459657","duration":"14182","realtime":"13492","%cpu":"65.1","%mem":"0.2","rss":"262524928","vmem":"2629632000","peak_rss":"262524928","peak_vmem":"2629677056","rchar":"20065323","wchar":"475475","syscr":"4353","syscw":"303","read_bytes":"74364928","write_bytes":"24576","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/ba\/641b5b511701a55b3d8d5be47aabf2","script":"\n    plot_coverage.R \"test.fastq2_bowtie2_mini\" \"read_nb_before\" \"2320711 2320942\" \"4627368 4627400\" \"5\" \"Ecoli Genome (bp)\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"plot_coverage_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"53131","inv_ctxt":"7"},{"task_id":"23","hash":"80\/45c1c5","native_id":"12523","process":"plot_coverage","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"plot_coverage (2)","status":"COMPLETED","exit":"0","submit":"1645716459664","start":"1645716459757","complete":"1645716473878","duration":"14214","realtime":"13570","%cpu":"64.7","%mem":"0.2","rss":"261111808","vmem":"2628239360","peak_rss":"261111808","peak_vmem":"2628280320","rchar":"20056608","wchar":"466811","syscr":"4353","syscw":"301","read_bytes":"74364928","write_bytes":"24576","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/80\/45c1c5ed8f207e8e37089d7f4cd765","script":"\n    plot_coverage.R \"test.fastq2_q20_mini\" \"read_nb_after\" \"2320711 2320942\" \"4627368 4627400\" \"5\" \"Ecoli Genome (bp)\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"plot_coverage_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"52674","inv_ctxt":"10"},{"task_id":"15","hash":"19\/cdb33c","native_id":"13248","process":"plot_read_length","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"plot_read_length (1)","status":"COMPLETED","exit":"0","submit":"1645716473885","start":"1645716473979","complete":"1645716489628","duration":"15743","realtime":"15022","%cpu":"68.1","%mem":"0.2","rss":"243191808","vmem":"2610286592","peak_rss":"243191808","peak_vmem":"2610331648","rchar":"20620878","wchar":"734698","syscr":"4663","syscw":"439","read_bytes":"74364928","write_bytes":"24576","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/19\/cdb33cb1bd91f9ba93b160feefbcb9","script":"\n    echo -e \'\n\\n\\n<br \/><br \/>\\n\\n###  Length of initial reads\\n\\n\n\\n\\n<\/center>\\n\\n\n![Figure 2: Frequency of reads according to read size (in bp).](.\/figures\/plot_read_length_ini.png){width=600}\n\\n\\n<\/center>\\n\\n\n\\n\\n<br \/><br \/>\\n\\n###  Length of reads after selection of attC in 5 prime \\n\\n\n\\n\\n<\/center>\\n\\n\n![Figure 3: Frequency of reads according to read size (in bp).](.\/figures\/plot_read_length_fivep_filtering.png){width=600}\n\\n\\n<\/center>\\n\\n\n\\n\\n<br \/><br \/>\\n\\n###  Length of reads after trimming \\n\\n\n\\n\\n<\/center>\\n\\n\n![Figure 4: Frequency of reads according to read size (in bp).](.\/figures\/plot_read_length_fivep_filtering_cut.png){width=600}\n\\n\\n<\/center>\\n\\n\n\\n\\n<br \/><br \/>\\n\\n###  Read length after cut-off\\n\\n\n\\n\\n<\/center>\\n\\n\n![Figure 5: Frequency of reads according to read size (in bp).](.\/figures\/plot_read_length_cutoff.png){width=600}\n\\n\\n<\/center>\\n\\n\n    \' > report.rmd\n    plot_read_length.R \"test.fastq2_ini.length\" \"test.fastq2_5pAttc.length\" \"test.fastq2_5pAtccRm.stat\" \"test.fastq2_cutoff.length\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"plot_read_length_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"53577","inv_ctxt":"9"},{"task_id":"13","hash":"26\/6dc1b9","native_id":"13971","process":"plot_fivep_filtering_stat","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"plot_fivep_filtering_stat (1)","status":"COMPLETED","exit":"0","submit":"1645716489635","start":"1645716489729","complete":"1645716504108","duration":"14473","realtime":"13810","%cpu":"65.2","%mem":"0.2","rss":"255778816","vmem":"2622439424","peak_rss":"255778816","peak_vmem":"2622480384","rchar":"20034479","wchar":"836210","syscr":"4346","syscw":"399","read_bytes":"74364928","write_bytes":"24576","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/26\/6dc1b980a8624b852450ebd1c8d7b8","script":"\n    echo -e \"\n\\n\\n<br \/><br \/>\\n\\n###  Base frequencies at the 5\' extremity of reads\\n\\n\n\\n\\n<\/center>\\n\\n\n![Figure 1: Frequency of each base at the 5\' of the reads.](.\/figures\/plot_fivep_filtering_stat.png){width=600}\n\\n\\n<\/center>\\n\\n\n    \" > report.rmd\n    plot_fivep_filtering_stat.R \"test.fastq2_5pAttc_1-51.stat\" \"CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"plot_fivep_filtering_stat_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"51189","inv_ctxt":"8"},{"task_id":"29","hash":"0d\/08f56c","native_id":"14700","process":"extract_seq","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bedtools_v2.30.0-gitlab_v8.0.img","tag":"-","name":"extract_seq (1)","status":"COMPLETED","exit":"0","submit":"1645716504115","start":"1645716504208","complete":"1645716505757","duration":"1642","realtime":"792","%cpu":"19.8","%mem":"0.0","rss":"6266880","vmem":"52637696","peak_rss":"6266880","peak_vmem":"52654080","rchar":"9503033","wchar":"4763829","syscr":"866","syscw":"3344","read_bytes":"6359040","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/0d\/08f56cb4703fae27a555e31a4e7d7b","script":"\n    # make a bed file from the reference genome\n    echo \">ref\" > tempo.ref.fasta\n    awk \'{lineKind=(NR-1)%2}lineKind==1{print $0}\' Ecoli-K12-MG1655_ORI_CENTERED.fasta >> tempo.ref.fasta |& tee extract_seq_report.txt\n    bedtools getfasta -fi tempo.ref.fasta -bed test.fastq2_around_insertion.bed -fo \"test.fastq2_around_insertion.fasta\" -name |& tee extract_seq_report.txt\n    rm tempo.ref.fasta\n    rm tempo.ref.fasta.fai\n    ","scratch":"-","queue":"-","cpus":"12","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"557","inv_ctxt":"0"},{"task_id":"30","hash":"1f\/a416f5","native_id":"14888","process":"random_insertion","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"random_insertion (1)","status":"COMPLETED","exit":"0","submit":"1645716505765","start":"1645716505857","complete":"1645716518627","duration":"12862","realtime":"11901","%cpu":"61.1","%mem":"0.4","rss":"403791872","vmem":"2905751552","peak_rss":"403791872","peak_vmem":"2905776128","rchar":"32197723","wchar":"1288929","syscr":"6293","syscw":"1485","read_bytes":"60127232","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/1f\/a416f56b3ed538dfed3b62c52333b4","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n### Random insertion sites\\n\\n\" > report.rmd\n    random_insertion.R \"test.fastq2_annot.pos\" \"motif_sites.pos\" \"2320711 2320942\" \"4627368 4627400\" \"G[AT]T\" \"4641652\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"random_insertion_report.txt\" \"report.rmd\"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n#### Insertion site counts\\n\\n\" > report.rmd\n    echo -e \'\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 14: Number of motifs insertion per fork](.\/figures\/plot_motif_insertion_per_fork.png){width=400}\n\\n\\n<\/center>\\n\\n\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 15: Number of motifs insertion per strand](.\/figures\/plot_motif_insertion_per_strand.png){width=400}\n\\n\\n<\/center>\\n\\n\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 16: Number of motifs insertion per strand](.\/figures\/plot_motif_insertion_per_strand.png){width=400}\n\\n\\n<\/center>\\n\\n\n    \' >> report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n#### Insertion site proportions\\n\\n\" >> report.rmd\n    echo -e \'\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 17: Proportion of motifs insertion per fork](.\/figures\/plot_motif_insertion_per_fork_prop.png){width=500}\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 18: Proportion of motifs insertion per strand](.\/figures\/plot_motif_insertion_per_strand_prop.png){width=500}\n\\n\\n<\/center>\\n\\n\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 19: Proportion of motifs insertion per strand](.\/figures\/plot_motif_insertion_per_fork_and_strand_prop.png){width=500}\n\\n\\n<\/center>\\n\\n\n    \' >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"62067","inv_ctxt":"70"},{"task_id":"31","hash":"57\/efb944","native_id":"14926","process":"base_freq","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"base_freq (1)","status":"COMPLETED","exit":"0","submit":"1645716505820","start":"1645716505868","complete":"1645716507386","duration":"1566","realtime":"88","%cpu":"11.6","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"286256","wchar":"17180","syscr":"526","syscw":"46","read_bytes":"279552","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/57\/efb94460322eaba9b4dc8af48daca3","script":"\n    # file splitting into seq\n    awk -v var1=LEADING_0 \'\n        {lineKind=(NR-1)%2}\n        lineKind==0{toGet=($0 ~ \">\" var1) ; next}\n        lineKind==1{if(toGet){print $0}}\n        \' test.fastq2_around_insertion.fasta > test.fastq2_LEADING_0.seq |& tee base_freq_report.txt\n    # ATGC contingency\n    gawk \'{\n        L=length($0);\n        for(i=1;i<=L;i++) {\n            B=substr($0,i,1);\n            T[i][B]++;\n        }\n      }\n      END{\n            for(BI=0;BI<5;BI++) {\n                B=(BI==0?\"A\":(BI==1?\"C\":(BI==2?\"G\":(BI==3?\"T\":\"Other\"))));\n                printf(\"%s\",B); \n                for(i in T) {\n                    tot=0.0;\n                    for(B2 in T[i]){\n                        tot+=T[i][B2];\n                    }\n                printf(\"\t%0.5f\",(T[i][B])); # T[i][B]\/tot for proportion\n                } \n            printf(\"\\n\");\n            }\n    }\' test.fastq2_LEADING_0.seq > test.fastq2_LEADING_0.stat |& tee base_freq_report.txt\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"33","hash":"eb\/7eacd6","native_id":"14959","process":"base_freq","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"base_freq (3)","status":"COMPLETED","exit":"0","submit":"1645716505837","start":"1645716505878","complete":"1645716507237","duration":"1400","realtime":"93","%cpu":"9.7","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"289206","wchar":"20165","syscr":"532","syscw":"52","read_bytes":"279552","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/eb\/7eacd60e5cb69b25030f58d71d06e3","script":"\n    # file splitting into seq\n    awk -v var1=LAGGING_0 \'\n        {lineKind=(NR-1)%2}\n        lineKind==0{toGet=($0 ~ \">\" var1) ; next}\n        lineKind==1{if(toGet){print $0}}\n        \' test.fastq2_around_insertion.fasta > test.fastq2_LAGGING_0.seq |& tee base_freq_report.txt\n    # ATGC contingency\n    gawk \'{\n        L=length($0);\n        for(i=1;i<=L;i++) {\n            B=substr($0,i,1);\n            T[i][B]++;\n        }\n      }\n      END{\n            for(BI=0;BI<5;BI++) {\n                B=(BI==0?\"A\":(BI==1?\"C\":(BI==2?\"G\":(BI==3?\"T\":\"Other\"))));\n                printf(\"%s\",B); \n                for(i in T) {\n                    tot=0.0;\n                    for(B2 in T[i]){\n                        tot+=T[i][B2];\n                    }\n                printf(\"\t%0.5f\",(T[i][B])); # T[i][B]\/tot for proportion\n                } \n            printf(\"\\n\");\n            }\n    }\' test.fastq2_LAGGING_0.seq > test.fastq2_LAGGING_0.stat |& tee base_freq_report.txt\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"34","hash":"3a\/64690b","native_id":"14996","process":"base_freq","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"base_freq (4)","status":"COMPLETED","exit":"0","submit":"1645716505855","start":"1645716505891","complete":"1645716507649","duration":"1794","realtime":"93","%cpu":"9.3","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"288556","wchar":"19497","syscr":"531","syscw":"51","read_bytes":"279552","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/3a\/64690b0eb4999e2ec36e7b519382f6","script":"\n    # file splitting into seq\n    awk -v var1=LAGGING_16 \'\n        {lineKind=(NR-1)%2}\n        lineKind==0{toGet=($0 ~ \">\" var1) ; next}\n        lineKind==1{if(toGet){print $0}}\n        \' test.fastq2_around_insertion.fasta > test.fastq2_LAGGING_16.seq |& tee base_freq_report.txt\n    # ATGC contingency\n    gawk \'{\n        L=length($0);\n        for(i=1;i<=L;i++) {\n            B=substr($0,i,1);\n            T[i][B]++;\n        }\n      }\n      END{\n            for(BI=0;BI<5;BI++) {\n                B=(BI==0?\"A\":(BI==1?\"C\":(BI==2?\"G\":(BI==3?\"T\":\"Other\"))));\n                printf(\"%s\",B); \n                for(i in T) {\n                    tot=0.0;\n                    for(B2 in T[i]){\n                        tot+=T[i][B2];\n                    }\n                printf(\"\t%0.5f\",(T[i][B])); # T[i][B]\/tot for proportion\n                } \n            printf(\"\\n\");\n            }\n    }\' test.fastq2_LAGGING_16.seq > test.fastq2_LAGGING_16.stat |& tee base_freq_report.txt\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"32","hash":"9d\/92f3fa","native_id":"15038","process":"base_freq","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"base_freq (2)","status":"COMPLETED","exit":"0","submit":"1645716505873","start":"1645716505957","complete":"1645716507549","duration":"1676","realtime":"91","%cpu":"11.3","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"288394","wchar":"19342","syscr":"530","syscw":"50","read_bytes":"279552","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/9d\/92f3fafcb69540040a3e761ae165c2","script":"\n    # file splitting into seq\n    awk -v var1=LEADING_16 \'\n        {lineKind=(NR-1)%2}\n        lineKind==0{toGet=($0 ~ \">\" var1) ; next}\n        lineKind==1{if(toGet){print $0}}\n        \' test.fastq2_around_insertion.fasta > test.fastq2_LEADING_16.seq |& tee base_freq_report.txt\n    # ATGC contingency\n    gawk \'{\n        L=length($0);\n        for(i=1;i<=L;i++) {\n            B=substr($0,i,1);\n            T[i][B]++;\n        }\n      }\n      END{\n            for(BI=0;BI<5;BI++) {\n                B=(BI==0?\"A\":(BI==1?\"C\":(BI==2?\"G\":(BI==3?\"T\":\"Other\"))));\n                printf(\"%s\",B); \n                for(i in T) {\n                    tot=0.0;\n                    for(B2 in T[i]){\n                        tot+=T[i][B2];\n                    }\n                printf(\"\t%0.5f\",(T[i][B])); # T[i][B]\/tot for proportion\n                } \n            printf(\"\\n\");\n            }\n    }\' test.fastq2_LEADING_16.seq > test.fastq2_LEADING_16.stat |& tee base_freq_report.txt\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"39","hash":"f5\/61649c","native_id":"15636","process":"report2","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-bash-extended_v4.0-gitlab_v8.0.img","tag":"-","name":"report2","status":"COMPLETED","exit":"0","submit":"1645716508657","start":"1645716508750","complete":"1645716509547","duration":"890","realtime":"20","%cpu":"14.2","%mem":"0.0","rss":"0","vmem":"0","peak_rss":"0","peak_vmem":"0","rchar":"133936","wchar":"1289","syscr":"245","syscw":"88","read_bytes":"242688","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/f5\/61649c0c7f840f663b69cce7d30a67","script":"\n    echo -e \"\n\\n\\n<br \/><br \/>\\n\\n###  Logos\\n\\n\n\\n\\nIn each sequence of length $((20 * 2)) <br \/>position $((20 + 1)) corresponds to the first nucleotide of the reference genome part of the read\n\" > report.rmd\n    count=0\n    for i in $(echo [test.fastq2_LAGGING_0, test.fastq2_LEADING_0, test.fastq2_LEADING_16, test.fastq2_LAGGING_16] | sed \'s\/^\\[\/\/\' | sed \'s\/\\]$\/\/\' | sed \'s\/,\/\/g\') ; do\n        echo -e \'\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure \'$((9 + $count))\': \'${i}\'](.\/figures\/logo_\'${i}\'.png){width=600}\n\\n\\n<\/center>\\n\\n\n        \' >> report.rmd\n        count=$((count + 1))\n    done\n    ","scratch":"-","queue":"-","cpus":"1","memory":"3221225472","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"0","inv_ctxt":"0"},{"task_id":"35","hash":"e9\/5d7f6b","native_id":"16267","process":"logo","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"logo (1)","status":"COMPLETED","exit":"0","submit":"1645716518644","start":"1645716518727","complete":"1645716527997","duration":"9353","realtime":"8655","%cpu":"60.8","%mem":"0.2","rss":"214171648","vmem":"2581831680","peak_rss":"214171648","peak_vmem":"2582380544","rchar":"15274154","wchar":"894677","syscr":"2843","syscw":"319","read_bytes":"55312384","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/e9\/5d7f6b630f133ea41b0775c518c2ab","script":"\n    logo.R \"test.fastq2_LAGGING_0.stat\" 20 \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"logo_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"53175","inv_ctxt":"10"},{"task_id":"36","hash":"4a\/a4f272","native_id":"16887","process":"logo","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"logo (2)","status":"COMPLETED","exit":"0","submit":"1645716528003","start":"1645716528097","complete":"1645716537157","duration":"9154","realtime":"8437","%cpu":"63.7","%mem":"0.2","rss":"216649728","vmem":"2584612864","peak_rss":"216649728","peak_vmem":"2585165824","rchar":"15274179","wchar":"1026299","syscr":"2871","syscw":"337","read_bytes":"55312384","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/4a\/a4f2724d73fbb88d0c824fd3f5885b","script":"\n    logo.R \"test.fastq2_LEADING_0.stat\" 20 \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"logo_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"54038","inv_ctxt":"6"},{"task_id":"37","hash":"fe\/c071c5","native_id":"17500","process":"logo","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"logo (3)","status":"COMPLETED","exit":"0","submit":"1645716537173","start":"1645716537257","complete":"1645716546408","duration":"9235","realtime":"8562","%cpu":"62.3","%mem":"0.2","rss":"215310336","vmem":"2581274624","peak_rss":"215310336","peak_vmem":"2581843968","rchar":"15274094","wchar":"873352","syscr":"2839","syscw":"320","read_bytes":"55312384","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/fe\/c071c5f5bca9d3ad4d2f467386cdf2","script":"\n    logo.R \"test.fastq2_LEADING_16.stat\" 20 \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"logo_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"53358","inv_ctxt":"10"},{"task_id":"38","hash":"af\/12f23f","native_id":"18109","process":"logo","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"logo (4)","status":"COMPLETED","exit":"0","submit":"1645716546415","start":"1645716546509","complete":"1645716555617","duration":"9202","realtime":"8543","%cpu":"61.6","%mem":"0.2","rss":"214044672","vmem":"2581942272","peak_rss":"214044672","peak_vmem":"2582519808","rchar":"15274057","wchar":"903827","syscr":"2835","syscw":"321","read_bytes":"55312384","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/af\/12f23f76aa02d162d9c88d7d5f170d","script":"\n    logo.R \"test.fastq2_LAGGING_16.stat\" 20 \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"logo_report.txt\"\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"53441","inv_ctxt":"6"},{"task_id":"40","hash":"62\/70e758","native_id":"18772","process":"global_logo","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"global_logo","status":"COMPLETED","exit":"0","submit":"1645716555624","start":"1645716555717","complete":"1645716565297","duration":"9673","realtime":"8950","%cpu":"63.1","%mem":"0.2","rss":"214941696","vmem":"2580537344","peak_rss":"215007232","peak_vmem":"2581057536","rchar":"15282794","wchar":"870708","syscr":"2848","syscw":"333","read_bytes":"55312384","write_bytes":"0","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/62\/70e75873aad2f8ee5986ea076a6293","script":"\n    global_logo.R \"test.fastq2_LAGGING_0.stat test.fastq2_LEADING_0.stat test.fastq2_LEADING_16.stat test.fastq2_LAGGING_16.stat\" test.fastq2 20 \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"global_logo_report.txt\"\n    echo -e \'\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure 13: test.fastq2 global logo](.\/figures\/global_logo_test.fastq2.png){width=600}\n\\n\\n<\/center>\\n\\n\n    \' >> report.rmd\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"53159","inv_ctxt":"11"},{"task_id":"41","hash":"e9\/ea5890","native_id":"19392","process":"plot_insertion","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"plot_insertion (1)","status":"COMPLETED","exit":"0","submit":"1645716565306","start":"1645716565398","complete":"1645716601328","duration":"36022","realtime":"35316","%cpu":"74.7","%mem":"0.9","rss":"1018216448","vmem":"3384504320","peak_rss":"1018216448","peak_vmem":"3384528896","rchar":"42236606","wchar":"10201623","syscr":"11091","syscw":"1836","read_bytes":"74364928","write_bytes":"24576","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/e9\/ea58902dc875e505f25b4dc8376a20","script":"\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n###  Insertion plots\\n\\n\" > report.rmd\n    plot_insertion.R \"obs_rd_insertions.pos\" \"obs_rd_insertions.freq\" \"2320711 2320942\" \"4627368 4627400\" \"Ecoli Genome (bp)\" \"4641652\" \"50000\" \"100\" \"test.fastq2\" \"https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\" \"plot_insertion_report.txt\"\n    echo -e \"\\n\\n####  Histograms\\n\\n\" >> report.rmd\n    echo -e \'\n\\n\\n<\/center>\\n\\n\n![Figure 20: Insertion site usage (total insertions).](.\/figures\/plot_test.fastq2_insertion_hist_tot.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n\n![Figure 21: Insertion site usage zoomed for sites with few insertions (total insertions).](.\/figures\/plot_test.fastq2_insertion_hist_tot_zoom.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n\n![Figure 22: Insertion site usage (forward strand).](.\/figures\/plot_test.fastq2_insertion_hist_forward.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n\n![Figure 23: Insertion site usage (reverse strand).](.\/figures\/plot_test.fastq2_insertion_hist_reverse.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n\n    \' >> report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n####  Raw frequencies\\n\\n\" >> report.rmd\n    echo -e \"\\n\\nSee the CL Labbook section 24.7.3 to explain the limitation around 100 bp\\n\" >> report.rmd\n    echo -e \'\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n\n![Figure 24: Raw insertion frequencies.](.\/figures\/plot_test.fastq2_insertion_raw.png){width=600}\n\\n\\n<\/center>\\n\\n<br \/><br \/>\\n\\n\n    \' >> report.rmd\n    echo -e \"\\n\\n<br \/><br \/>\\n\\n####  Binned frequencies\\n\\n\" >> report.rmd\n    count=1\n    for i in 50000 ; do\n        echo -e \'\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure \'$((24 + $count))\': frequencies using the binning range of \'$(printf \"%\'d\" ${i})\'](.\/figures\/plot_test.fastq2_insertion_bin_\'${i}\'.png){width=600}\n\\n\\n<\/center>\\n\\n\n        \' >> report.rmd\n        count=$((count + 1))\n        echo -e \'\n\\n\\n<br \/><br \/>\\n\\n<\/center>\\n\\n\n![Figure \'$((24 + $count))\': frequencies using the binning range of \'$(printf \"%\'d\" ${i})\'](.\/figures\/plot_test.fastq2_lead_lag_insertion_bin_\'${i}\'.png){width=600}\n\\n\\n<\/center>\\n\\n\n        \' >> report.rmd\n        count=$((count + 1))\n    done\n    ","scratch":"-","queue":"-","cpus":"1","memory":"68719476736","disk":"-","time":"-","env":"git_path=https:\/\/gitlab.pasteur.fr\/gmillot\/14985_loot\/\nin_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\nfastq_file=test.fastq2.gz\nkraken_db=\/pasteur\/zeus\/services\/p01\/banques-prod\/prod\/rel\/kraken_standard\/current\/kraken\/2.1.1\/standard\/\nprimer_fasta=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/20200520_adapters_TruSeq_B2699_14985_CL.fasta\nalientrimmer_l_param=30\nattc_seq=CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG\nfivep_seq_filtering=^CAATTCATTCAAGCCGACGCCGCTTCGCGGCGCGGCTTAATTCAAGCG.+$\nfivep_seq_nb=48\nadded_nb=3\ncutoff_nb=25\nref_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/dataset\/coli_K12_MG1655_NC_000913.3_ORI_CENTERED\/\nref_file=Ecoli-K12-MG1655_ORI_CENTERED.fasta\nori_coord=2320711 2320942\nter_coord=4627368 4627400\ncolor_coverage=5\nxlab=Ecoli Genome (bp)\ngenome_size=4641652\ninsertion_dist=20\nmotif_fw=G[AT]T\nmotif_rev=A[AT]C\nwindow_size=50000\nstep=100\ncute_path=https:\/\/gitlab.pasteur.fr\/gmillot\/cute_little_R_functions\/-\/raw\/v11.0.0\/cute_little_R_functions.R\nsystem_exec=local\nout_path=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/results\/20220120_test_1645716342\nPATH=\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/bin:$PATH\n","error_action":"-","vol_ctxt":"72034","inv_ctxt":"18"},{"task_id":"42","hash":"fe\/324ee1","native_id":"20358","process":"print_report","module":"-","container":"\/mnt\/c\/Users\/Gael\/Documents\/singularity\/gmillot-r_v4.0.5_extended_v2.0-gitlab_v6.4.img","tag":"-","name":"print_report (1)","status":"COMPLETED","exit":"0","submit":"1645716601618","start":"1645716601628","complete":"1645716611407","duration":"9789","realtime":"9031","%cpu":"57.7","%mem":"0.3","rss":"237260800","vmem":"1102451912704","peak_rss":"237260800","peak_vmem":"1102518943744","rchar":"32759956","wchar":"12187216","syscr":"5119","syscw":"1054","read_bytes":"54798336","write_bytes":"4096","attempt":"1","workdir":"\/mnt\/c\/Users\/Gael\/Documents\/Git_projects\/14985_loot\/work\/fe\/324ee16ee402fe906db95b0a4d8470","script":"\n    cp report.rmd report_file.rmd # this is to get hard files, not symlinks\n    mkdir figures\n    mkdir files\n    mkdir reports\n    cat stat_tempo > .\/files\/test.fastq2_5pAttc_1-51.stat # this is to get hard files, not symlinks\n    cp head.fw.txt head.rv.txt table1.txt table2.txt table3.txt table4.txt table8.txt .\/files\/ # this is to get hard files, not symlinks\n    cp plot_fivep_filtering_stat.png plot_read_length_cutoff.png plot_read_length_fivep_filtering.png plot_read_length_fivep_filtering_cut.png plot_read_length_ini.png plot_test.fastq2_q20_nodup_mini.png plot_test.fastq2_bowtie2_mini.png plot_test.fastq2_q20_mini.png logo_test.fastq2_LAGGING_0.png logo_test.fastq2_LEADING_0.png logo_test.fastq2_LEADING_16.png logo_test.fastq2_LAGGING_16.png global_logo_test.fastq2.png plot_motif_insertion_per_fork.png plot_motif_insertion_per_fork_and_strand.png plot_motif_insertion_per_fork_and_strand_prop.png plot_motif_insertion_per_fork_prop.png plot_motif_insertion_per_strand.png plot_motif_insertion_per_strand_prop.png plot_test.fastq2_insertion_bin_50000.png plot_test.fastq2_insertion_hist_forward.png plot_test.fastq2_insertion_hist_reverse.png plot_test.fastq2_insertion_hist_tot.png plot_test.fastq2_insertion_hist_tot_zoom.png plot_test.fastq2_insertion_raw.png plot_test.fastq2_lead_lag_insertion_bin_50000.png .\/figures\/ # Warning several files\n    cp plot_fivep_filtering_stat.png .\/reports\/nf_dag.png # trick to delude the knitting during 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diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nf_timeline.html b/example_of_result/20220120_test_1645716342/reports/nf_timeline.html
similarity index 95%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nf_timeline.html
rename to example_of_result/20220120_test_1645716342/reports/nf_timeline.html
index 2802bf55aaab6aa07575c61de47dc05ce73a78ca..0a7f3a491da9a029401337ad0872dd097d4ea8dd 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/nf_timeline.html
+++ b/example_of_result/20220120_test_1645716342/reports/nf_timeline.html
@@ -205,52 +205,52 @@ $(function() {
 
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-        {"label": "print_report (1)", "cached": false, "index": 31, "times": [{"starting_time": 1645559070332, "ending_time": 1645559070367}, {"starting_time": 1645559070367, "ending_time": 1645559080074, "label": "10.5s \/ 243.9 MB"}, {"starting_time": 1645559080074, "ending_time": 1645559080807}]}
+        {"label": "backup", "cached": false, "index": 0, "times": [{"starting_time": 1645716348774, "ending_time": 1645716348848}, {"starting_time": 1645716348848, "ending_time": 1645716348861, "label": "1.5s \/ 0"}, {"starting_time": 1645716348861, "ending_time": 1645716350250}]},
+        {"label": "Nremove (1)", "cached": false, "index": 1, "times": [{"starting_time": 1645716348799, "ending_time": 1645716348863}, {"starting_time": 1645716348863, "ending_time": 1645716349298, "label": "1.9s \/ 12.1 MB"}, {"starting_time": 1645716349298, "ending_time": 1645716350697}]},
+        {"label": "init", "cached": false, "index": 2, "times": [{"starting_time": 1645716348822, "ending_time": 1645716348876}, {"starting_time": 1645716348876, "ending_time": 1645716348887, "label": "1.6s \/ 0"}, {"starting_time": 1645716348887, "ending_time": 1645716350408}]},
+        {"label": "report1", "cached": false, "index": 3, "times": [{"starting_time": 1645716348846, "ending_time": 1645716348890}, {"starting_time": 1645716348890, "ending_time": 1645716348910, "label": "1.7s \/ 0"}, {"starting_time": 1645716348910, "ending_time": 1645716350548}]},
+        {"label": "workflowVersion", "cached": false, "index": 4, "times": [{"starting_time": 1645716348869, "ending_time": 1645716348948}, {"starting_time": 1645716348948, "ending_time": 1645716349659, "label": "2.2s \/ 4.9 MB"}, {"starting_time": 1645716349659, "ending_time": 1645716351088}]},
+        {"label": "trim (1)", "cached": false, "index": 5, "times": [{"starting_time": 1645716358514, "ending_time": 1645716358599}, {"starting_time": 1645716358599, "ending_time": 1645716360709, "label": "3s \/ 38.7 MB"}, {"starting_time": 1645716360709, "ending_time": 1645716361558}]},
+        {"label": "kraken (1)", "cached": false, "index": 6, "times": [{"starting_time": 1645716361603, "ending_time": 1645716361657}, {"starting_time": 1645716361657, "ending_time": 1645716361666, "label": "89ms \/ 0"}, {"starting_time": 1645716361666, "ending_time": 1645716361692}]},
+        {"label": "fivep_filtering (1)", "cached": false, "index": 7, "times": [{"starting_time": 1645716361621, "ending_time": 1645716361668}, {"starting_time": 1645716361668, "ending_time": 1645716363626, "label": "2.9s \/ 9.6 MB"}, {"starting_time": 1645716363626, "ending_time": 1645716364528}]},
+        {"label": "cutoff (1)", "cached": false, "index": 8, "times": [{"starting_time": 1645716364576, "ending_time": 1645716364629}, {"starting_time": 1645716364629, "ending_time": 1645716365369, "label": "1.8s \/ 9.7 MB"}, {"starting_time": 1645716365369, "ending_time": 1645716366378}]},
+        {"label": "fastqc1 (1)", "cached": false, "index": 9, "times": [{"starting_time": 1645716369105, "ending_time": 1645716369181}, {"starting_time": 1645716369181, "ending_time": 1645716375790, "label": "7.7s \/ 159.6 MB"}, {"starting_time": 1645716375790, "ending_time": 1645716376788}]},
+        {"label": "fastqc2 (1)", "cached": false, "index": 10, "times": [{"starting_time": 1645716369125, "ending_time": 1645716369205}, {"starting_time": 1645716369205, "ending_time": 1645716375833, "label": "7.7s \/ 149.8 MB"}, {"starting_time": 1645716375833, "ending_time": 1645716376867}]},
+        {"label": "bowtie2 (1)", "cached": false, "index": 11, "times": [{"starting_time": 1645716372936, "ending_time": 1645716372987}, {"starting_time": 1645716372987, "ending_time": 1645716376670, "label": "4.8s \/ 114.6 MB"}, {"starting_time": 1645716376670, "ending_time": 1645716377778}]},
+        {"label": "multiQC", "cached": false, "index": 12, "times": [{"starting_time": 1645716383461, "ending_time": 1645716383484}, {"starting_time": 1645716383484, "ending_time": 1645716392484, "label": "9s \/ 75.1 MB"}, {"starting_time": 1645716392484, "ending_time": 1645716392498}]},
+        {"label": "Q20 (1)", "cached": false, "index": 13, "times": [{"starting_time": 1645716383680, "ending_time": 1645716383684}, {"starting_time": 1645716383684, "ending_time": 1645716384099, "label": "1.6s \/ 5.8 MB"}, {"starting_time": 1645716384099, "ending_time": 1645716385238}]},
+        {"label": "coverage (1)", "cached": false, "index": 14, "times": [{"starting_time": 1645716384875, "ending_time": 1645716384885}, {"starting_time": 1645716384885, "ending_time": 1645716385770, "label": "1.9s \/ 5 MB"}, {"starting_time": 1645716385770, "ending_time": 1645716386798}]},
+        {"label": "no_soft_clipping (1)", "cached": false, "index": 15, "times": [{"starting_time": 1645716386298, "ending_time": 1645716386340}, {"starting_time": 1645716386340, "ending_time": 1645716386680, "label": "1.6s \/ 5.3 MB"}, {"starting_time": 1645716386680, "ending_time": 1645716387937}]},
+        {"label": "duplicate_removal (1)", "cached": false, "index": 16, "times": [{"starting_time": 1645716386318, "ending_time": 1645716386352}, {"starting_time": 1645716386352, "ending_time": 1645716388559, "label": "3.5s \/ 7.6 MB"}, {"starting_time": 1645716388559, "ending_time": 1645716389847}]},
+        {"label": "coverage (2)", "cached": false, "index": 14, "times": [{"starting_time": 1645716386840, "ending_time": 1645716386898}, {"starting_time": 1645716386898, "ending_time": 1645716387811, "label": "2.2s \/ 5 MB"}, {"starting_time": 1645716387811, "ending_time": 1645716389018}]},
+        {"label": "insertion (1)", "cached": false, "index": 17, "times": [{"starting_time": 1645716389880, "ending_time": 1645716389948}, {"starting_time": 1645716389948, "ending_time": 1645716390557, "label": "1.8s \/ 9 MB"}, {"starting_time": 1645716390557, "ending_time": 1645716391698}]},
+        {"label": "coverage (3)", "cached": false, "index": 14, "times": [{"starting_time": 1645716389899, "ending_time": 1645716389959}, {"starting_time": 1645716389959, "ending_time": 1645716390803, "label": "2s \/ 5.1 MB"}, {"starting_time": 1645716390803, "ending_time": 1645716391917}]},
+        {"label": "seq_around_insertion (1)", "cached": false, "index": 18, "times": [{"starting_time": 1645716403767, "ending_time": 1645716403811}, {"starting_time": 1645716403811, "ending_time": 1645716409459, "label": "6.4s \/ 156.4 MB"}, {"starting_time": 1645716409459, "ending_time": 1645716410157}]},
+        {"label": "motif", "cached": false, "index": 19, "times": [{"starting_time": 1645716410167, "ending_time": 1645716410257}, {"starting_time": 1645716410257, "ending_time": 1645716424169, "label": "14.6s \/ 217.9 MB"}, {"starting_time": 1645716424169, "ending_time": 1645716424798}]},
+        {"label": "final_insertion_files (1)", "cached": false, "index": 20, "times": [{"starting_time": 1645716424805, "ending_time": 1645716424898}, {"starting_time": 1645716424898, "ending_time": 1645716430545, "label": "6.4s \/ 157.3 MB"}, {"starting_time": 1645716430545, "ending_time": 1645716431207}]},
+        {"label": "plot_coverage (3)", "cached": false, "index": 21, "times": [{"starting_time": 1645716431216, "ending_time": 1645716431308}, {"starting_time": 1645716431308, "ending_time": 1645716444882, "label": "14.3s \/ 249.2 MB"}, {"starting_time": 1645716444882, "ending_time": 1645716445468}]},
+        {"label": "plot_coverage (1)", "cached": false, "index": 21, "times": [{"starting_time": 1645716445475, "ending_time": 1645716445568}, {"starting_time": 1645716445568, "ending_time": 1645716459060, "label": "14.2s \/ 250.4 MB"}, {"starting_time": 1645716459060, "ending_time": 1645716459657}]},
+        {"label": "plot_coverage (2)", "cached": false, "index": 21, "times": [{"starting_time": 1645716459664, "ending_time": 1645716459757}, {"starting_time": 1645716459757, "ending_time": 1645716473327, "label": "14.2s \/ 249 MB"}, {"starting_time": 1645716473327, "ending_time": 1645716473878}]},
+        {"label": "plot_read_length (1)", "cached": false, "index": 22, "times": [{"starting_time": 1645716473885, "ending_time": 1645716473979}, {"starting_time": 1645716473979, "ending_time": 1645716489001, "label": "15.7s \/ 231.9 MB"}, {"starting_time": 1645716489001, "ending_time": 1645716489628}]},
+        {"label": "plot_fivep_filtering_stat (1)", "cached": false, "index": 23, "times": [{"starting_time": 1645716489635, "ending_time": 1645716489729}, {"starting_time": 1645716489729, "ending_time": 1645716503539, "label": "14.5s \/ 243.9 MB"}, {"starting_time": 1645716503539, "ending_time": 1645716504108}]},
+        {"label": "extract_seq (1)", "cached": false, "index": 24, "times": [{"starting_time": 1645716504115, "ending_time": 1645716504208}, {"starting_time": 1645716504208, "ending_time": 1645716505000, "label": "1.6s \/ 6 MB"}, {"starting_time": 1645716505000, "ending_time": 1645716505757}]},
+        {"label": "random_insertion (1)", "cached": false, "index": 25, "times": [{"starting_time": 1645716505765, "ending_time": 1645716505857}, {"starting_time": 1645716505857, "ending_time": 1645716517758, "label": "12.9s \/ 385.1 MB"}, {"starting_time": 1645716517758, "ending_time": 1645716518627}]},
+        {"label": "base_freq (1)", "cached": false, "index": 26, "times": [{"starting_time": 1645716505820, "ending_time": 1645716505868}, {"starting_time": 1645716505868, "ending_time": 1645716505956, "label": "1.6s \/ 0"}, {"starting_time": 1645716505956, "ending_time": 1645716507386}]},
+        {"label": "base_freq (3)", "cached": false, "index": 26, "times": [{"starting_time": 1645716505837, "ending_time": 1645716505878}, {"starting_time": 1645716505878, "ending_time": 1645716505971, "label": "1.4s \/ 0"}, {"starting_time": 1645716505971, "ending_time": 1645716507237}]},
+        {"label": "base_freq (4)", "cached": false, "index": 26, "times": [{"starting_time": 1645716505855, "ending_time": 1645716505891}, {"starting_time": 1645716505891, "ending_time": 1645716505984, "label": "1.8s \/ 0"}, {"starting_time": 1645716505984, "ending_time": 1645716507649}]},
+        {"label": "base_freq (2)", "cached": false, "index": 26, "times": [{"starting_time": 1645716505873, "ending_time": 1645716505957}, {"starting_time": 1645716505957, "ending_time": 1645716506048, "label": "1.7s \/ 0"}, {"starting_time": 1645716506048, "ending_time": 1645716507549}]},
+        {"label": "report2", "cached": false, "index": 27, "times": [{"starting_time": 1645716508657, "ending_time": 1645716508750}, {"starting_time": 1645716508750, "ending_time": 1645716508770, "label": "890ms \/ 0"}, {"starting_time": 1645716508770, "ending_time": 1645716509547}]},
+        {"label": "logo (1)", "cached": false, "index": 28, "times": [{"starting_time": 1645716518644, "ending_time": 1645716518727}, {"starting_time": 1645716518727, "ending_time": 1645716527382, "label": "9.4s \/ 204.2 MB"}, {"starting_time": 1645716527382, "ending_time": 1645716527997}]},
+        {"label": "logo (2)", "cached": false, "index": 28, "times": [{"starting_time": 1645716528003, "ending_time": 1645716528097}, {"starting_time": 1645716528097, "ending_time": 1645716536534, "label": "9.2s \/ 206.6 MB"}, {"starting_time": 1645716536534, "ending_time": 1645716537157}]},
+        {"label": "logo (3)", "cached": false, "index": 28, "times": [{"starting_time": 1645716537173, "ending_time": 1645716537257}, {"starting_time": 1645716537257, "ending_time": 1645716545819, "label": "9.2s \/ 205.3 MB"}, {"starting_time": 1645716545819, "ending_time": 1645716546408}]},
+        {"label": "logo (4)", "cached": false, "index": 28, "times": [{"starting_time": 1645716546415, "ending_time": 1645716546509}, {"starting_time": 1645716546509, "ending_time": 1645716555052, "label": "9.2s \/ 204.1 MB"}, {"starting_time": 1645716555052, "ending_time": 1645716555617}]},
+        {"label": "global_logo", "cached": false, "index": 29, "times": [{"starting_time": 1645716555624, "ending_time": 1645716555717}, {"starting_time": 1645716555717, "ending_time": 1645716564667, "label": "9.7s \/ 205 MB"}, {"starting_time": 1645716564667, "ending_time": 1645716565297}]},
+        {"label": "plot_insertion (1)", "cached": false, "index": 30, "times": [{"starting_time": 1645716565306, "ending_time": 1645716565398}, {"starting_time": 1645716565398, "ending_time": 1645716600714, "label": "36s \/ 971 MB"}, {"starting_time": 1645716600714, "ending_time": 1645716601328}]},
+        {"label": "print_report (1)", "cached": false, "index": 31, "times": [{"starting_time": 1645716601618, "ending_time": 1645716601628}, {"starting_time": 1645716601628, "ending_time": 1645716610659, "label": "9.8s \/ 226.3 MB"}, {"starting_time": 1645716610659, "ending_time": 1645716611407}]}
     ]
 }
 ;
diff --git a/example_of_result/20220120_test_1645716342/reports/nf_trace.txt b/example_of_result/20220120_test_1645716342/reports/nf_trace.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9ea13ed2fd18480b2580cce7dbd80f5750367967
--- /dev/null
+++ b/example_of_result/20220120_test_1645716342/reports/nf_trace.txt
@@ -0,0 +1,43 @@
+task_id	hash	native_id	name	status	exit	submit	duration	realtime	%cpu	peak_rss	peak_vmem	rchar	wchar
+5	6b/c7fecc	3736	backup	COMPLETED	0	2022-02-24 16:25:48.774	1.5s	13ms	5.5%	0	0	104.3 KB	500 B
+1	bf/506112	3796	init	COMPLETED	0	2022-02-24 16:25:48.822	1.6s	11ms	5.3%	0	0	104.1 KB	665 B
+3	4b/1f154d	3854	report1	COMPLETED	0	2022-02-24 16:25:48.846	1.7s	20ms	4.9%	0	0	104.4 KB	679 B
+2	0a/e411b8	3764	Nremove (1)	COMPLETED	0	2022-02-24 16:25:48.799	1.9s	435ms	45.9%	12.1 MB	70.6 MB	16.8 MB	14.5 MB
+6	03/f78123	3906	workflowVersion	COMPLETED	0	2022-02-24 16:25:48.869	2.2s	711ms	11.8%	4.9 MB	38.4 MB	133.3 KB	2.1 KB
+7	31/65ff8a	4579	trim (1)	COMPLETED	0	2022-02-24 16:25:58.514	3s	2.1s	44.2%	38.7 MB	5.6 GB	16.4 MB	12 MB
+10	b2/dfc998	4993	kraken (1)	COMPLETED	0	2022-02-24 16:26:01.603	89ms	9ms	41.0%	0	0	150.8 KB	220 B
+9	fa/c1fd48	5007	fivep_filtering (1)	COMPLETED	0	2022-02-24 16:26:01.621	2.9s	2s	21.5%	9.6 MB	61.4 MB	28 MB	15.3 MB
+11	c9/fb815c	5361	cutoff (1)	COMPLETED	0	2022-02-24 16:26:04.576	1.8s	740ms	15.7%	9.7 MB	61.3 MB	7 MB	3.9 MB
+8	dc/1c3599	5579	fastqc1 (1)	COMPLETED	0	2022-02-24 16:26:09.105	7.7s	6.6s	50.3%	159.6 MB	3.1 GB	13.9 MB	1.2 MB
+12	16/720a57	5600	fastqc2 (1)	COMPLETED	0	2022-02-24 16:26:09.125	7.7s	6.6s	48.5%	149.8 MB	3.1 GB	12.2 MB	1.2 MB
+14	ea/2dce38	6271	bowtie2 (1)	COMPLETED	0	2022-02-24 16:26:12.936	4.8s	3.7s	51.4%	114.6 MB	239.5 MB	35 MB	16.2 MB
+16	09/3abd99	7440	Q20 (1)	COMPLETED	0	2022-02-24 16:26:23.680	1.6s	415ms	16.5%	5.8 MB	42.8 MB	3.2 MB	2.2 MB
+17	44/53399e	7603	coverage (1)	COMPLETED	0	2022-02-24 16:26:24.875	1.9s	885ms	15.7%	5 MB	44.6 MB	479.6 KB	91 KB
+21	cd/ab90a7	7933	no_soft_clipping (1)	COMPLETED	0	2022-02-24 16:26:26.298	1.6s	340ms	10.8%	5.3 MB	57.6 MB	2.1 MB	1.5 MB
+19	36/3097aa	8065	coverage (2)	COMPLETED	0	2022-02-24 16:26:26.840	2.2s	913ms	13.8%	5 MB	44.4 MB	335 KB	82.4 KB
+20	c1/88ba17	7953	duplicate_removal (1)	COMPLETED	0	2022-02-24 16:26:26.318	3.5s	2.2s	23.3%	7.6 MB	53 MB	12.9 MB	6.6 MB
+24	19/def24f	8911	insertion (1)	COMPLETED	0	2022-02-24 16:26:29.880	1.8s	609ms	17.5%	9 MB	65.6 MB	2.5 MB	1.7 MB
+25	e4/43c3da	8932	coverage (3)	COMPLETED	0	2022-02-24 16:26:29.899	2s	844ms	14.8%	5.1 MB	44.6 MB	310.2 KB	82.1 KB
+18	93/1153d4	7377	multiQC	COMPLETED	0	2022-02-24 16:26:23.461	9s	9s	37.1%	75.1 MB	85.3 MB	28.3 MB	2.3 MB
+27	fa/585809	9449	seq_around_insertion (1)	COMPLETED	0	2022-02-24 16:26:43.767	6.4s	5.6s	70.2%	156.4 MB	2.3 GB	17.9 MB	229.4 KB
+4	64/dc0f4b	9899	motif	COMPLETED	0	2022-02-24 16:26:50.167	14.6s	13.9s	65.4%	217.9 MB	2.4 GB	48.3 MB	39.7 MB
+26	95/7e25d2	10621	final_insertion_files (1)	COMPLETED	0	2022-02-24 16:27:04.805	6.4s	5.6s	70.8%	157.3 MB	2.3 GB	18 MB	266 KB
+28	2c/4408b4	11081	plot_coverage (3)	COMPLETED	0	2022-02-24 16:27:11.216	14.3s	13.6s	64.6%	249.2 MB	2.4 GB	19.1 MB	459.1 KB
+22	ba/641b5b	11803	plot_coverage (1)	COMPLETED	0	2022-02-24 16:27:25.475	14.2s	13.5s	65.1%	250.4 MB	2.4 GB	19.1 MB	464.3 KB
+23	80/45c1c5	12523	plot_coverage (2)	COMPLETED	0	2022-02-24 16:27:39.664	14.2s	13.6s	64.7%	249 MB	2.4 GB	19.1 MB	455.9 KB
+15	19/cdb33c	13248	plot_read_length (1)	COMPLETED	0	2022-02-24 16:27:53.885	15.7s	15s	68.1%	231.9 MB	2.4 GB	19.7 MB	717.5 KB
+13	26/6dc1b9	13971	plot_fivep_filtering_stat (1)	COMPLETED	0	2022-02-24 16:28:09.635	14.5s	13.8s	65.2%	243.9 MB	2.4 GB	19.1 MB	816.6 KB
+29	0d/08f56c	14700	extract_seq (1)	COMPLETED	0	2022-02-24 16:28:24.115	1.6s	792ms	19.8%	6 MB	50.2 MB	9.1 MB	4.5 MB
+33	eb/7eacd6	14959	base_freq (3)	COMPLETED	0	2022-02-24 16:28:25.837	1.4s	93ms	9.7%	0	0	282.4 KB	19.7 KB
+31	57/efb944	14926	base_freq (1)	COMPLETED	0	2022-02-24 16:28:25.820	1.6s	88ms	11.6%	0	0	279.5 KB	16.8 KB
+32	9d/92f3fa	15038	base_freq (2)	COMPLETED	0	2022-02-24 16:28:25.873	1.7s	91ms	11.3%	0	0	281.6 KB	18.9 KB
+34	3a/64690b	14996	base_freq (4)	COMPLETED	0	2022-02-24 16:28:25.855	1.8s	93ms	9.3%	0	0	281.8 KB	19 KB
+39	f5/61649c	15636	report2	COMPLETED	0	2022-02-24 16:28:28.657	890ms	20ms	14.2%	0	0	130.8 KB	1.3 KB
+30	1f/a416f5	14888	random_insertion (1)	COMPLETED	0	2022-02-24 16:28:25.765	12.9s	11.9s	61.1%	385.1 MB	2.7 GB	30.7 MB	1.2 MB
+35	e9/5d7f6b	16267	logo (1)	COMPLETED	0	2022-02-24 16:28:38.644	9.4s	8.7s	60.8%	204.2 MB	2.4 GB	14.6 MB	873.7 KB
+36	4a/a4f272	16887	logo (2)	COMPLETED	0	2022-02-24 16:28:48.003	9.2s	8.4s	63.7%	206.6 MB	2.4 GB	14.6 MB	1002.2 KB
+37	fe/c071c5	17500	logo (3)	COMPLETED	0	2022-02-24 16:28:57.173	9.2s	8.6s	62.3%	205.3 MB	2.4 GB	14.6 MB	852.9 KB
+38	af/12f23f	18109	logo (4)	COMPLETED	0	2022-02-24 16:29:06.415	9.2s	8.5s	61.6%	204.1 MB	2.4 GB	14.6 MB	882.6 KB
+40	62/70e758	18772	global_logo	COMPLETED	0	2022-02-24 16:29:15.624	9.7s	9s	63.1%	205 MB	2.4 GB	14.6 MB	850.3 KB
+41	e9/ea5890	19392	plot_insertion (1)	COMPLETED	0	2022-02-24 16:29:25.306	36s	35.3s	74.7%	971 MB	3.2 GB	40.3 MB	9.7 MB
+42	fe/324ee1	20358	print_report (1)	COMPLETED	0	2022-02-24 16:30:01.618	9.8s	9s	57.7%	226.3 MB	1 TB	31.2 MB	11.6 MB
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/plot_cov_report.txt b/example_of_result/20220120_test_1645716342/reports/plot_cov_report.txt
similarity index 96%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/plot_cov_report.txt
rename to example_of_result/20220120_test_1645716342/reports/plot_cov_report.txt
index 39f7b79c1ceffc4a1b502c801f5b80d603aef4c9..c7df686c59d61aa5b8a49262c11ea8b2861bf8c3 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/plot_cov_report.txt
+++ b/example_of_result/20220120_test_1645716342/reports/plot_cov_report.txt
@@ -12,7 +12,7 @@
 
 
 
-2022-02-22 20:41:57
+2022-02-24 16:27:16
 
 
 
@@ -31,12 +31,12 @@
 
 
 
-END TIME: 2022-02-22 20:42:06
+END TIME: 2022-02-24 16:27:25
 
 
 
 
-TOTAL TIME LAPSE: 9S
+TOTAL TIME LAPSE: 8S
 
 
 
@@ -120,9 +120,9 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 20:42:06
+TIME: 2022-02-24 16:27:25
 
-TOTAL TIME LAPSE: 9S
+TOTAL TIME LAPSE: 8S
 
 
 
@@ -140,7 +140,7 @@ TOTAL TIME LAPSE: 9S
 
 
 
-2022-02-22 20:41:13
+2022-02-24 16:27:45
 
 
 
@@ -159,12 +159,12 @@ TOTAL TIME LAPSE: 9S
 
 
 
-END TIME: 2022-02-22 20:41:22
+END TIME: 2022-02-24 16:27:53
 
 
 
 
-TOTAL TIME LAPSE: 9S
+TOTAL TIME LAPSE: 8S
 
 
 
@@ -192,9 +192,9 @@ erase.objects      TRUE
 erase.graphs       TRUE 
 script             plot_coverage 
 run.way            SCRIPT 
-command            /usr/lib/R/bin/exec/R,--no-echo,--no-restore,--file=/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/bin/plot_coverage.R,--args,test.fastq2_bowtie2_mini,read_nb_before,2320711 2320942,4627368 4627400,5,Ecoli Genome (bp),test.fastq2,https://gitlab.pasteur.fr/gmillot/cute_little_R_functions/-/raw/v11.0.0/cute_little_R_functions.R,plot_coverage_report.txt 
-cov                test.fastq2_bowtie2_mini 
-read_nb            read_nb_before 
+command            /usr/lib/R/bin/exec/R,--no-echo,--no-restore,--file=/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/bin/plot_coverage.R,--args,test.fastq2_q20_mini,read_nb_after,2320711 2320942,4627368 4627400,5,Ecoli Genome (bp),test.fastq2,https://gitlab.pasteur.fr/gmillot/cute_little_R_functions/-/raw/v11.0.0/cute_little_R_functions.R,plot_coverage_report.txt 
+cov                test.fastq2_q20_mini 
+read_nb            read_nb_after 
 ori_coord          2320711 2320942 
 ter_coord          4627368 4627400 
 color_coverage     5 
@@ -248,9 +248,9 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 20:41:22
+TIME: 2022-02-24 16:27:53
 
-TOTAL TIME LAPSE: 9S
+TOTAL TIME LAPSE: 8S
 
 
 
@@ -268,7 +268,7 @@ TOTAL TIME LAPSE: 9S
 
 
 
-2022-02-22 20:41:28
+2022-02-24 16:27:31
 
 
 
@@ -287,12 +287,12 @@ TOTAL TIME LAPSE: 9S
 
 
 
-END TIME: 2022-02-22 20:41:37
+END TIME: 2022-02-24 16:27:39
 
 
 
 
-TOTAL TIME LAPSE: 9S
+TOTAL TIME LAPSE: 8S
 
 
 
@@ -320,9 +320,9 @@ erase.objects      TRUE
 erase.graphs       TRUE 
 script             plot_coverage 
 run.way            SCRIPT 
-command            /usr/lib/R/bin/exec/R,--no-echo,--no-restore,--file=/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/bin/plot_coverage.R,--args,test.fastq2_q20_mini,read_nb_after,2320711 2320942,4627368 4627400,5,Ecoli Genome (bp),test.fastq2,https://gitlab.pasteur.fr/gmillot/cute_little_R_functions/-/raw/v11.0.0/cute_little_R_functions.R,plot_coverage_report.txt 
-cov                test.fastq2_q20_mini 
-read_nb            read_nb_after 
+command            /usr/lib/R/bin/exec/R,--no-echo,--no-restore,--file=/mnt/c/Users/Gael/Documents/Git_projects/14985_loot/bin/plot_coverage.R,--args,test.fastq2_bowtie2_mini,read_nb_before,2320711 2320942,4627368 4627400,5,Ecoli Genome (bp),test.fastq2,https://gitlab.pasteur.fr/gmillot/cute_little_R_functions/-/raw/v11.0.0/cute_little_R_functions.R,plot_coverage_report.txt 
+cov                test.fastq2_bowtie2_mini 
+read_nb            read_nb_before 
 ori_coord          2320711 2320942 
 ter_coord          4627368 4627400 
 color_coverage     5 
@@ -376,9 +376,9 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 20:41:37
+TIME: 2022-02-24 16:27:39
 
-TOTAL TIME LAPSE: 9S
+TOTAL TIME LAPSE: 8S
 
 
 
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/plot_fivep_filtering_stat_report.txt b/example_of_result/20220120_test_1645716342/reports/plot_fivep_filtering_stat_report.txt
similarity index 96%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/plot_fivep_filtering_stat_report.txt
rename to example_of_result/20220120_test_1645716342/reports/plot_fivep_filtering_stat_report.txt
index 022c05811c55bc9d500e9db5cad22cd34808c015..acc666b6c96d6e679732052385e1c0e9808c4c60 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/plot_fivep_filtering_stat_report.txt
+++ b/example_of_result/20220120_test_1645716342/reports/plot_fivep_filtering_stat_report.txt
@@ -12,7 +12,7 @@
 
 
 
-2022-02-22 15:21:55
+2022-02-24 16:28:15
 
 
 
@@ -31,12 +31,12 @@
 
 
 
-END TIME: 2022-02-22 15:22:03
+END TIME: 2022-02-24 16:28:23
 
 
 
 
-TOTAL TIME LAPSE: 9S
+TOTAL TIME LAPSE: 8S
 
 
 
@@ -115,9 +115,9 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 15:22:03
+TIME: 2022-02-24 16:28:23
 
-TOTAL TIME LAPSE: 9S
+TOTAL TIME LAPSE: 8S
 
 
 
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/plot_insertion_report.txt b/example_of_result/20220120_test_1645716342/reports/plot_insertion_report.txt
similarity index 97%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/plot_insertion_report.txt
rename to example_of_result/20220120_test_1645716342/reports/plot_insertion_report.txt
index 4e7dd6b12764040a9f6c3fc8239d7c1f6249f4ca..027d7141a96fdd8b136904cc89dc7f54c1c50f9f 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/plot_insertion_report.txt
+++ b/example_of_result/20220120_test_1645716342/reports/plot_insertion_report.txt
@@ -12,7 +12,7 @@
 
 
 
-2022-02-22 20:43:15
+2022-02-24 16:29:30
 
 
 
@@ -31,7 +31,7 @@
 
 
 
-END TIME: 2022-02-22 20:43:46
+END TIME: 2022-02-24 16:30:00
 
 
 
@@ -122,7 +122,7 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 20:43:46
+TIME: 2022-02-24 16:30:00
 
 TOTAL TIME LAPSE: 30S
 
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/plot_read_length_report.txt b/example_of_result/20220120_test_1645716342/reports/plot_read_length_report.txt
similarity index 97%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/plot_read_length_report.txt
rename to example_of_result/20220120_test_1645716342/reports/plot_read_length_report.txt
index 5ba0bb128d0817e99d9b1617da46f3611a42c3b9..a9078b4936c076395229258c75a1a5c22384773e 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/plot_read_length_report.txt
+++ b/example_of_result/20220120_test_1645716342/reports/plot_read_length_report.txt
@@ -12,7 +12,7 @@
 
 
 
-2022-02-22 20:40:48
+2022-02-24 16:27:59
 
 
 
@@ -31,7 +31,7 @@
 
 
 
-END TIME: 2022-02-22 20:40:58
+END TIME: 2022-02-24 16:28:09
 
 
 
@@ -117,7 +117,7 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 20:40:58
+TIME: 2022-02-24 16:28:09
 
 TOTAL TIME LAPSE: 10S
 
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/print_report.txt b/example_of_result/20220120_test_1645716342/reports/print_report.txt
similarity index 97%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/print_report.txt
rename to example_of_result/20220120_test_1645716342/reports/print_report.txt
index f3cb917aed3d69ebe31ef96f9905e67968f997e7..e92dcdfeb426b6da121052e189c60ce6b3e82b49 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/print_report.txt
+++ b/example_of_result/20220120_test_1645716342/reports/print_report.txt
@@ -12,7 +12,7 @@
 
 
 
-2022-02-22 20:44:35
+2022-02-24 16:30:06
 
 
 
@@ -31,7 +31,7 @@
 
 
 
-END TIME: 2022-02-22 20:44:40
+END TIME: 2022-02-24 16:30:10
 
 
 
@@ -113,7 +113,7 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 20:44:40
+TIME: 2022-02-24 16:30:10
 
 TOTAL TIME LAPSE: 4S
 
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/q20_report.txt b/example_of_result/20220120_test_1645716342/reports/q20_report.txt
similarity index 100%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/q20_report.txt
rename to example_of_result/20220120_test_1645716342/reports/q20_report.txt
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/random_insertion_report.txt b/example_of_result/20220120_test_1645716342/reports/random_insertion_report.txt
similarity index 97%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/random_insertion_report.txt
rename to example_of_result/20220120_test_1645716342/reports/random_insertion_report.txt
index 4a417d698b00a02e68f99fe68ac98057a29dc947..7f145d7756e542332a4871cb231268481e9709a8 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/random_insertion_report.txt
+++ b/example_of_result/20220120_test_1645716342/reports/random_insertion_report.txt
@@ -12,7 +12,7 @@
 
 
 
-2022-02-22 20:42:14
+2022-02-24 16:28:32
 
 
 
@@ -31,7 +31,7 @@
 
 
 
-END TIME: 2022-02-22 20:42:21
+END TIME: 2022-02-24 16:28:38
 
 
 
@@ -121,7 +121,7 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 20:42:21
+TIME: 2022-02-24 16:28:38
 
 TOTAL TIME LAPSE: 6S
 
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/report.rmd b/example_of_result/20220120_test_1645716342/reports/report.rmd
similarity index 86%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/report.rmd
rename to example_of_result/20220120_test_1645716342/reports/report.rmd
index 2c06de6711a251c40a122dc1dbc961c4be2bcdb6..40af493fb4f5ee2dac7d41ee55506fea37bd5ba7 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/report.rmd
+++ b/example_of_result/20220120_test_1645716342/reports/report.rmd
@@ -32,7 +32,7 @@ Ratio:
 
 
 AlienTrimmer main options: -k 10 -l 30 -m 5 -q 20 -p 0 (Phred+33)  /  26 alien sequence(s)  /  810 k-mers (k=10)
-<br />[00:02]       8,932 reads processed:       4,767 trimmed         223 removed
+<br />[00:00]       8,932 reads processed:       4,767 trimmed         223 removed
 <br /><br />AlienTrimmer also removes reads according to quality criteria
 
 Number of sequence before trimming: 8,932
@@ -231,15 +231,15 @@ Analysis complete for test.fastq2_5pAtccRm.fq
 Time loading reference: 00:00:00
 <br />Time loading forward index: 00:00:00
 <br />Time loading mirror index: 00:00:00
-<br />Multiseed full-index search: 00:00:00
+<br />Multiseed full-index search: 00:00:01
 <br />3742 reads; of these:
 <br />  3742 (100.00%) were unpaired; of these:
 <br />    1240 (33.14%) aligned 0 times
 <br />    2308 (61.68%) aligned exactly 1 time
 <br />    194 (5.18%) aligned >1 times
 <br />66.86% overall alignment rate
-<br />Time searching: 00:00:00
-<br />Overall time: 00:00:00
+<br />Time searching: 00:00:01
+<br />Overall time: 00:00:01
 
 
 <br /><br />
@@ -384,7 +384,7 @@ In each sequence of length 40 <br />position 21 corresponds to the first nucleot
 </center>
 
 
-![Figure 9: test.fastq2_LEADING_0](./figures/logo_test.fastq2_LEADING_0.png){width=600}
+![Figure 9: test.fastq2_LAGGING_0](./figures/logo_test.fastq2_LAGGING_0.png){width=600}
 
 
 </center>
@@ -399,7 +399,7 @@ In each sequence of length 40 <br />position 21 corresponds to the first nucleot
 </center>
 
 
-![Figure 10: test.fastq2_LAGGING_16](./figures/logo_test.fastq2_LAGGING_16.png){width=600}
+![Figure 10: test.fastq2_LEADING_0](./figures/logo_test.fastq2_LEADING_0.png){width=600}
 
 
 </center>
@@ -414,7 +414,7 @@ In each sequence of length 40 <br />position 21 corresponds to the first nucleot
 </center>
 
 
-![Figure 11: test.fastq2_LAGGING_0](./figures/logo_test.fastq2_LAGGING_0.png){width=600}
+![Figure 11: test.fastq2_LEADING_16](./figures/logo_test.fastq2_LEADING_16.png){width=600}
 
 
 </center>
@@ -429,7 +429,7 @@ In each sequence of length 40 <br />position 21 corresponds to the first nucleot
 </center>
 
 
-![Figure 12: test.fastq2_LEADING_16](./figures/logo_test.fastq2_LEADING_16.png){width=600}
+![Figure 12: test.fastq2_LAGGING_16](./figures/logo_test.fastq2_LAGGING_16.png){width=600}
 
 
 </center>
@@ -854,8 +854,6 @@ See the CL Labbook section 24.7.3 to explain the limitation around 100 bp
 See the [reports](./reports) folder for all the details of the analysis, including the parameters used in the .config file
 
 
-<br /><br />
-
 Full .nextflow.log is in: /mnt/c/Users/Gael/Documents/Git_projects/14985_loot<br />The one in the [reports](./reports) folder is not complete (miss the end)
 
 
@@ -864,34 +862,50 @@ Full .nextflow.log is in: /mnt/c/Users/Gael/Documents/Git_projects/14985_loot<br
 ###  Workflow Version
 
 
-Project (empty means no .git folder where the main.nf file is present):  loot https://gitlab.pasteur.fr/gmillot/14985_loot (fetch)
-<br />Git info (empty means no .git folder where the main.nf file is present):  v7.7.0-dirty
-<br />Cmd line: nextflow run main.nf -resume
-<br />execution mode: local
-<br />Manifest's pipeline version: null
-<br />result path: /mnt/c/Users/Gael/Documents/Git_projects/14985_loot/results/20220120_res_CL14985_B4985_4_1645559065
-<br />nextflow version: 21.04.2
+
+
+#### GENERAL
+
+
+| Variable | Value |
+| :-- | :-- |
+| Project<br />(empty means no .git folder where the main.nf file is present) | loot	https://gitlab.pasteur.fr/gmillot/14985_loot (fetch) | # works only if the main script run is located in a directory that has a .git folder, i.e., that is connected to a distant repo
+| Git info<br />(empty means no .git folder where the main.nf file is present) | v7.9.0-dirty | # idem. Provide the small commit number of the script and nextflow.config used in the execution
+| Cmd line | nextflow run main.nf -resume |
+| execution mode | local |
+| Manifest's pipeline version | null |
+| result path | /mnt/c/Users/Gael/Documents/Git_projects/14985_loot/results/20220120_test_1645716342 |
+| nextflow version | 21.04.2 |
+    
 
 
 <br /><br />
 
-IMPLICIT VARIABLES:
+#### IMPLICIT VARIABLES
+
 
-launchDir (directory where the workflow is run): /mnt/c/Users/Gael/Documents/Git_projects/14985_loot<br />
-projectDir (directory where the main.nf script is located): /mnt/c/Users/Gael/Documents/Git_projects/14985_loot<br />
-workDir (directory where tasks temporary files are created): /mnt/c/Users/Gael/Documents/Git_projects/14985_loot/work
+| Name | Description | Value | 
+| :-- | :-- | :-- |
+| launchDir | Directory where the workflow is run | /mnt/c/Users/Gael/Documents/Git_projects/14985_loot |
+| nprojectDir | Directory where the main.nf script is located | /mnt/c/Users/Gael/Documents/Git_projects/14985_loot |
+| workDir | Directory where tasks temporary files are created | /mnt/c/Users/Gael/Documents/Git_projects/14985_loot/work |
+    
 
 
 <br /><br />
 
-USER VARIABLES:<br />
+#### USER VARIABLES
 
-out_path: /mnt/c/Users/Gael/Documents/Git_projects/14985_loot/results/20220120_res_CL14985_B4985_4_1645559065<br />
-in_path: /mnt/c/Users/Gael/Documents/Git_projects/14985_loot/dataset
+
+| Name | Description | Value | 
+| :-- | :-- | :-- |
+| out_path | output folder path | /mnt/c/Users/Gael/Documents/Git_projects/14985_loot/results/20220120_test_1645716342 |
+| in_path | input folder path | /mnt/c/Users/Gael/Documents/Git_projects/14985_loot/dataset |
+    
 
 
 <br /><br />
 
-WORKFLOW DIAGRAM:<br />
+#### WORKFLOW DIAGRAM
 
 See the [nf_dag.png](./reports/nf_dag.png) file
diff --git a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/seq_around_insertion_report.txt b/example_of_result/20220120_test_1645716342/reports/seq_around_insertion_report.txt
similarity index 97%
rename from example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/seq_around_insertion_report.txt
rename to example_of_result/20220120_test_1645716342/reports/seq_around_insertion_report.txt
index d35209b3ec428a5f3cb4493450167dc38565875b..53d3a5b48609f77228cfa9374e4cca47556caa40 100644
--- a/example_of_result/20220120_res_CL14985_B4985_4_1645559065/reports/seq_around_insertion_report.txt
+++ b/example_of_result/20220120_test_1645716342/reports/seq_around_insertion_report.txt
@@ -12,7 +12,7 @@
 
 
 
-2022-02-22 20:41:44
+2022-02-24 16:26:49
 
 
 
@@ -31,7 +31,7 @@
 
 
 
-END TIME: 2022-02-22 20:41:44
+END TIME: 2022-02-24 16:26:49
 
 
 
@@ -118,7 +118,7 @@ loaded via a namespace (and not attached):
 
 ################################ JOB END
 
-TIME: 2022-02-22 20:41:44
+TIME: 2022-02-24 16:26:49
 
 TOTAL TIME LAPSE: 0S
 
diff --git a/main.nf b/main.nf
index 86d60a84045107c7eac6b6a19c5caed8eae29333..f15bc2c070a03220aa99b97b70e7e0d33e20eec9 100755
--- a/main.nf
+++ b/main.nf
@@ -1057,21 +1057,41 @@ process workflowVersion { // create a file with the workflow version in out_path
 
     script:
     """
-    echo -e "\\n\\n<br /><br />\\n\\n###  Workflow Version\\n\\n" > report.rmd
-    echo -e "\\n\\nGENERAL:\\n\\nProject (empty means no .git folder where the main.nf file is present): " \$(git -C ${projectDir} remote -v | head -n 1) >> report.rmd # works only if the main script run is located in a directory that has a .git folder, i.e., that is connected to a distant repo
-    echo "<br />Git info (empty means no .git folder where the main.nf file is present): " \$(git -C ${projectDir} describe --abbrev=10 --dirty --always --tags) >> report.rmd # idem. Provide the small commit number of the script and nextflow.config used in the execution
-    echo "<br />Cmd line: ${workflow.commandLine}" >> report.rmd
-    echo "<br />execution mode": ${system_exec} >> report.rmd
     modules=$modules # this is just to deal with variable interpretation during the creation of the .command.sh file by nextflow. See also \$modules below
+    echo -e "\\n\\n<br /><br />\\n\\n###  Workflow Version\\n\\n" > report.rmd
+    echo -e "\\n\\n#### General\\n\\n
+| Variable | Value |
+| :-- | :-- |
+| Project<br />(empty means no .git folder where the main.nf file is present) | \$(git -C ${projectDir} remote -v | head -n 1) | # works only if the main script run is located in a directory that has a .git folder, i.e., that is connected to a distant repo
+| Git info<br />(empty means no .git folder where the main.nf file is present) | \$(git -C ${projectDir} describe --abbrev=10 --dirty --always --tags) | # idem. Provide the small commit number of the script and nextflow.config used in the execution
+| Cmd line | ${workflow.commandLine} |
+| execution mode | ${system_exec} |" >> report.rmd 
+
     if [[ ! -z \$modules ]] ; then
-        echo "<br />loaded modules (according to specification by the user thanks to the --modules argument of main.nf)": ${modules} >> report.rmd
+        echo "| loaded modules (according to specification by the user thanks to the --modules argument of main.nf) | ${modules} |" >> report.rmd
     fi
-    echo "<br />Manifest's pipeline version: ${workflow.manifest.version}" >> report.rmd
-    echo "<br />result path: ${out_path}" >> report.rmd
-    echo "<br />nextflow version: ${nextflow.version}" >> report.rmd
-    echo -e "\\n\\n<br /><br />\\n\\nIMPLICIT VARIABLES:\\n\\nlaunchDir (directory where the workflow is run): ${launchDir}<br />\\nprojectDir (directory where the main.nf script is located): ${projectDir}<br />\\nworkDir (directory where tasks temporary files are created): ${workDir}" >> report.rmd
-    echo -e "\\n\\n<br /><br />\\n\\nUSER VARIABLES:<br />\\n\\nout_path: ${out_path}<br />\\nin_path: ${in_path}" >> report.rmd
-    echo -e "\\n\\n<br /><br />\\n\\nWORKFLOW DIAGRAM:<br />\\n\\nSee the [nf_dag.png](./reports/nf_dag.png) file" >> report.rmd
+    
+    echo "| Manifest's pipeline version | ${workflow.manifest.version} |
+| result path | ${out_path} |
+| nextflow version | ${nextflow.version} |
+    " >> report.rmd
+
+    echo -e "\\n\\n<br /><br />\\n\\n#### Implicit variables\\n\\n
+| Name | Description | Value | 
+| :-- | :-- | :-- |
+| launchDir | Directory where the workflow is run | ${launchDir} |
+| nprojectDir | Directory where the main.nf script is located | ${projectDir} |
+| workDir | Directory where tasks temporary files are created | ${workDir} |
+    " >> report.rmd
+
+    echo -e "\\n\\n<br /><br />\\n\\n#### User variables\\n\\n
+| Name | Description | Value | 
+| :-- | :-- | :-- |
+| out_path | output folder path | ${out_path} |
+| in_path | input folder path | ${in_path} |
+    " >> report.rmd
+
+    echo -e "\\n\\n<br /><br />\\n\\n#### Workflow diagram\\n\\nSee the [nf_dag.png](./reports/nf_dag.png) file" >> report.rmd
     """
 }
 //${projectDir} nextflow variable
diff --git a/nextflow.config b/nextflow.config
index 18806d4e654673e56512a9249e8a54064d699916..1354d0397f9f90bd27ca1086919b398ceb67ee9d 100755
--- a/nextflow.config
+++ b/nextflow.config
@@ -73,14 +73,14 @@ env {
 //////// variables that will be used below (and potentially in the main.nf file)
 
 //// must be also exported
-system_exec = 'local' // the system that runs the workflow. Either 'local' or 'slurm'
+system_exec = 'local' // the system that runs the workflow. Either 'local' or 'slurm' or 'slurm_local' (test using the head of the cluster)
 //docker_exe = true // true for docker and false for singularity
 //out_path="/mnt/c/Users/Gael/Desktop" // where the report file will be saved. Example report_path = '.' for where the main.nf run is executed or report_path = '/mnt/c/Users/Gael/Desktop' 
 out_path="$baseDir/results" // where the report file will be saved. Example report_path = '.' for where the main.nf run is executed or report_path = '/mnt/c/Users/Gael/Desktop' 
 //// end must be also exported
 
 //// general variables
-result_folder_name="20220120_res_CL14985_B4985_4"
+result_folder_name="20220120_test"
 //// end general variables
 
 //// slurm variables
@@ -159,16 +159,18 @@ dag {
 singularity {
     enabled = true
     autoMounts = true // automatically mounts host paths in the executed container
-    if(system_exec == 'slurm'){
+    if(system_exec == 'slurm' || system_exec == 'slurm_local'){
         runOptions = '--no-home --bind /pasteur'
     }else{
-        runOptions = '--no-home'
+        runOptions = '--no-home' // --no-home prevent singularity to mount the $HOME path and thus forces singularity to work with only what is inside the container
     }
     //runOptions = '--home $HOME:/home/$USER --bind /pasteur' // provide any extra command line options supported by the singularity exec. Here, fait un bind de tout /pasteur dans /pasteur du container. Sinon pas d accès
     if(system_exec == 'slurm'){
         cacheDir = '/pasteur/zeus/projets/p01/BioIT/gmillot/14985_loot/singularity' // name of the directory where remote Singularity images are stored. When rerun, the exec directly uses these without redownloading them. When using a computing cluster it must be a shared folder accessible to all computing nodes
+    }else if(system_exec == 'slurm_local'){
+        cacheDir = 'singularity' // "$baseDir/singularity" can be used but do not forget double quotes.
     }else{
-        cacheDir = 'singularity'
+        cacheDir = '/mnt/c/Users/Gael/Documents/singularity' // "$baseDir/singularity" can be used but do not forget double quotes.
     }
 }