Merge branch 'master' into 'dev'

# Conflicts:
#   Snakefile

README.md

@@ -12,7 +12,7 @@
 
 # What is ePeak ?
 
-ePeak is a snakemake-based workflow for the analysis of ChIP-seq data from raw FASTQ files to differential analysis of transcription factor binding or histone modification marking. It streamlines critical steps like the quality assessment of the immunoprecipitation using the cross correlation and the replicate comparison for both narrow and broad peaks. For the differential analysis ePeak provides linear and non linear methods for normalisation between samples as well as conservative and stringent models for estimating the variance and testing the significance of the observed differences (see [chipflowr](https://gitlab.pasteur.fr/hub/chipflowr)).
+ePeak is a snakemake-based workflow for the analysis of ChIP-seq/CUT&RUN/CUT&Tag data from raw FASTQ files to differential analysis of transcription factor binding or histone modification marking. It streamlines critical steps like the quality assessment of the immunoprecipitation using the cross correlation and the replicate comparison for both narrow and broad peaks. For the differential analysis ePeak provides linear and non linear methods for normalisation between samples as well as conservative and stringent models for estimating the variance and testing the significance of the observed differences (see [chipflowr](https://gitlab.pasteur.fr/hub/chipflowr)).
 
 <img src="images/epeak_workflow.svg" width="700">
 
@@ -306,9 +306,9 @@ intersectionApproach:
 
 ```
 
-### Default mode for cut&run
+### Default mode for CUT&RUN/CUT&Tag
 
-With cut&run data, make deduplication only on INPUT/IgG data (dedup_IP to False). Then perform a stringent peak calling with SEACR and use Intersection Approach. Overlapping parameter of IA on peaks is set at 0.8.
+With CUT&RUN/CUT&Tag data, make deduplication only on INPUT/IgG data (dedup_IP to False). Then perform a stringent peak calling with SEACR and use Intersection Approach. Overlapping parameter of IA on peaks is set at 0.8. Set SEACR normalization to non if experiment have control genome (a scaling factor will be calulated from spike-in) .
 
 ```
 mark_duplicates:

config/config.yaml

@@ -58,7 +58,7 @@ design:
     marks: K4Me3
     condition: C, U
     replicates: Rep
-    spike: yes
+    spike: no
     spike_genome_file: /path/to/genome/directory/dmel9.fa
 
 #===============================================================================
@@ -252,10 +252,10 @@ intersectionApproach:
 #
 # :Parameters:
 #
-# - method: 'Limma' or 'DEseq2'
+# - method: 'Limma' or 'DESeq2'
 # - spikes: If you have spikes, set to 'yes' will use spike normalization
 # - normalization: 'geometrical', 'spikes', 'scale', 'quantile', 'cyclicloess'
-# - pAdjustMethod: Limma and DEseq2 options. For Limma, 'none', 'BH', 'BY' and 'holm' are possible.
+# - pAdjustMethod: Limma and DESeq2 options. For Limma, 'none', 'BH', 'BY' and 'holm' are possible.
 #                  For DESeq2, 'holm', 'hochberg', 'hommel', 'bonferroni', 'BH', 'BY', 'fdr' and 'none' are accepted.
 # - alpha: threshold for differential analysis. Default: 0.05
 # - batch: NULL or a vector with batch effects as c("","")
@@ -304,7 +304,7 @@ bamCoverage:
 #===============================================================================
 
 geneBody:
-    do: yes
+    do: no
     regionsFileName: /path/to/genome/directory/mm10_genemodel.bed
     threads: 4