diff --git a/phagetermvirome/PhageTerm.py b/phagetermvirome/PhageTerm.py
index e9104cc8396894f015a16745d3cc3774182c597f..dc1593f39138ba717e688541cc5ca0effee5187b 100755
--- a/phagetermvirome/PhageTerm.py
+++ b/phagetermvirome/PhageTerm.py
@@ -142,7 +142,7 @@ def main():
host_whole_coverage = return_dict[core_id][5]
list_hybrid = return_dict[core_id][6]
insert = return_dict[core_id][7].tolist()
- paired_missmatch = return_dict[core_id][8]
+ paired_mismatch = return_dict[core_id][8]
reads_tested = return_dict[core_id][9]
else:
termini_coverage += return_dict[core_id][0]
@@ -153,7 +153,7 @@ def main():
host_whole_coverage += return_dict[core_id][5]
list_hybrid += return_dict[core_id][6]
insert += return_dict[core_id][7].tolist()
- paired_missmatch += return_dict[core_id][8]
+ paired_mismatch += return_dict[core_id][8]
reads_tested += return_dict[core_id][9]
termini_coverage = termini_coverage.tolist()
diff --git a/phagetermvirome/functions_PhageTerm.py b/phagetermvirome/functions_PhageTerm.py
index c9e9b8249ea5b0407fd961f6cd5f710abd5c927c..0a941a169f270e91967bf8c0eedea4503dfbc4d5 100644
--- a/phagetermvirome/functions_PhageTerm.py
+++ b/phagetermvirome/functions_PhageTerm.py
@@ -88,7 +88,7 @@ def init_ws(p_res,refseq,hostseq):
host_whole_coverage = np.array([host_len*[0], host_len*[0]])
list_hybrid = np.array([0,0])
insert = []
- paired_missmatch = 0
+ paired_mismatch = 0
read_match = 0
else:
termini_coverage=p_res.interm_res.termini_coverage
@@ -99,12 +99,12 @@ def init_ws(p_res,refseq,hostseq):
host_whole_coverage=p_res.interm_res.host_whole_coverage
list_hybrid=p_res.interm_res.list_hybrid
insert=p_res.interm_res.insert
- paired_missmatch=p_res.interm_res.paired_mismatch
+ paired_mismatch=p_res.interm_res.paired_mismatch
k=int(p_res.interm_res.reads_tested)
#count_line=p_res.count_line-1 # do that because readsCoverage will start by incrementing it of 1
read_match=p_res.read_match
return gen_len,host_len,termini_coverage,whole_coverage,paired_whole_coverage,phage_hybrid_coverage,host_hybrid_coverage, \
- host_whole_coverage,list_hybrid,insert,paired_missmatch,k,count_line,read_match #TODO refactor that.
+ host_whole_coverage,list_hybrid,insert,paired_mismatch,k,count_line,read_match #TODO refactor that.
@@ -198,7 +198,7 @@ def readsCoverage(inRawDArgs,refseq,inDArgs,fParms,return_dict, core_id,line_sta
position_end = matchPplus_end_paired
insert.append(insert_length)
else:
- paired_missmatch += 1
+ paired_mismatch += 1
# Paired hybrid
if inDArgs.hostseq != "" and matchPplus_start_paired == -1:
matchHplus_start, matchHplus_end = applyCoverage(read_paired[:fParms.seed], inDArgs.hostseq)
@@ -258,7 +258,7 @@ def readsCoverage(inRawDArgs,refseq,inDArgs,fParms,return_dict, core_id,line_sta
position_start = matchPminus_start_paired
insert.append(insert_length)
else:
- paired_missmatch += 1
+ paired_mismatch += 1
# Paired hybrid
if inDArgs.hostseq != "" and matchPminus_start_paired == -1:
matchHplus_start, matchHplus_end = applyCoverage(read_paired[:fParms.seed], inDArgs.hostseq)
@@ -318,7 +318,7 @@ def readsCoverage(inRawDArgs,refseq,inDArgs,fParms,return_dict, core_id,line_sta
chk_handler.check(count_line,core_id,idx_refseq,termini_coverage,whole_coverage,paired_whole_coverage,\
phage_hybrid_coverage, host_hybrid_coverage, \
- host_whole_coverage,list_hybrid,insert,paired_missmatch,k,read_match) # maybe time to create checkpoint
+ host_whole_coverage,list_hybrid,insert,paired_mismatch,k,read_match) # maybe time to create checkpoint
else:
if line[0] == "@":
@@ -356,13 +356,13 @@ def readsCoverage(inRawDArgs,refseq,inDArgs,fParms,return_dict, core_id,line_sta
host_hybrid_coverage = correctEdge(host_hybrid_coverage, fParms.edge)
if return_dict!=None and tParms.dir_cov_mm==None:
- return_dict[core_id] = [termini_coverage, whole_coverage, paired_whole_coverage, phage_hybrid_coverage, host_hybrid_coverage, host_whole_coverage, list_hybrid, np.array(insert), paired_missmatch, k]
+ return_dict[core_id] = [termini_coverage, whole_coverage, paired_whole_coverage, phage_hybrid_coverage, host_hybrid_coverage, host_whole_coverage, list_hybrid, np.array(insert), paired_mismatch, k]
elif return_dict==None and tParms.dir_cov_mm!=None:
insert = np.array(insert)
fic_name = os.path.join(tParms.dir_cov_mm, "coverage" + str(idx_refseq) + "_" + str(core_id))
res=RCRes(termini_coverage,whole_coverage,paired_whole_coverage,\
phage_hybrid_coverage, host_hybrid_coverage, \
- host_whole_coverage,list_hybrid,insert,paired_missmatch,k)
+ host_whole_coverage,list_hybrid,insert,paired_mismatch,k)
res.save(fic_name)
else:
print("Error: readsCoverage must be used either with directory name or return_dict")
@@ -1087,7 +1087,7 @@ def CreateReport(phagename, seed, added_whole_coverage, draw, Redundant, P_left,
report.append(Paragraph(ptext, styles["Left"]))
report.append(Spacer(1, 10))
- ptext = '<i><font size=10>PhageTerm software uses raw reads of a phage sequenced with a sequencing technology using random fragmentation and its genomic reference sequence to determine the termini position. The process starts with the alignment of NGS reads to the phage genome in order to calculate the starting position coverage (SPC), where a hit is given only to the position of the first base in a successfully aligned read (the alignment algorithm uses the lenght of the seed (default: 20) for mapping and does not accept gap or missmatch to speed up the process). Then the program apply 2 distinct scoring methods: i) a statistical approach based on the Gamma law; and ii) a method derived from LI and al. 2014 paper.</font></i>'
+ ptext = '<i><font size=10>PhageTerm software uses raw reads of a phage sequenced with a sequencing technology using random fragmentation and its genomic reference sequence to determine the termini position. The process starts with the alignment of NGS reads to the phage genome in order to calculate the starting position coverage (SPC), where a hit is given only to the position of the first base in a successfully aligned read (the alignment algorithm uses the lenght of the seed (default: 20) for mapping and does not accept gap or mismatch to speed up the process). Then the program apply 2 distinct scoring methods: i) a statistical approach based on the Gamma law; and ii) a method derived from LI and al. 2014 paper.</font></i>'
report.append(Paragraph(ptext, styles["Justify"]))
report.append(Spacer(1, 5))