def runSam2bam(inFile, outFile, log, index=True, sort=True, delinFile=False, onlyUnique=False, onlyProperPaired=False, filterMQ=0, L=None, threads=1, verbose=False, dry=False):
if(delinFile and files_exist(outFile) and not files_exist(inFile)):
print("Skipping sam2bam for " + outFile, file=log)
else:
if(onlyUnique and filterMQ == 0):
filterMQ = 1;
success = True
cmd = [getBinary("samtools"), "view", "-@", str(threads), "-Sb", "-o", outFile, inFile]
if filterMQ > 0:
cmd+=["-q", str(filterMQ)]
if onlyProperPaired:
cmd+=["-f", "2"]
if not L is None:
cmd+=["-L", L]
run(" ".join(cmd), log, verbose=verbose, dry=dry)
if(sort):
tmp = outFile + "_tmp"
if(not dry):
os.rename(outFile, tmp)
run(" ".join([getBinary("samtools"), "sort", "-@", str(threads), "-o", outFile, tmp]), log, verbose=verbose, dry=dry)
if(success):
removeFile(tmp)
if(success and delinFile):
if(not dry):
removeFile(inFile)
if(index):
pysamIndex(outFile)
def runSam2bam(inFile,
outFile,
log,
index=True,
sort=None,
delinFile=False,
onlyUnique=False,
onlyProperPaired=False,
filterMQ=0,
L=None,
threads=1,
verbose=False,
dry=False):
if delinFile and files_exist(outFile) and not files_exist(inFile):
print("Skipping sam2bam for %s" % outFile, file=log)
else:
if onlyUnique and filterMQ == 0:
filterMQ = 1
success = True
cmd = [
"samtools view", "-@",
str(threads), "-Sb", "-o", outFile, inFile
]
if filterMQ > 0:
cmd += ["-q", str(filterMQ)]
if onlyProperPaired:
cmd += ["-f", "2"]
if L is not None:
cmd += ["-L", L]
run(" ".join(cmd), log, verbose=verbose, dry=dry)
if sort is not None:
tmp = outFile + "_tmp"
if not dry:
os.rename(outFile, tmp)
if sort.lower() == "index":
run(" ".join(
["samtools sort", "-@",
str(threads), "-o", outFile, tmp]),
log,
verbose=verbose,
dry=dry)
elif sort.lower() == "name":
run(" ".join([
"samtools sort -n", "-@",
str(threads), "-o", outFile, tmp
]),
log,
verbose=verbose,
dry=dry)
if success:
removeFile(tmp)
if success and delinFile:
if not dry:
removeFile(inFile)
if index:
pysamIndex(outFile)
def genomewideReadSeparation(referenceFile, snpsFile, bam, minBaseQual, outputBAMPrefix, conversionThreshold, log):
ref = pysam.FastaFile(referenceFile)
snps = SNPtools.SNPDictionary(snpsFile)
snps.read()
# Go through one chr after the other
testFile = SlamSeqBamFile(bam, referenceFile, snps)
samFile = pysam.AlignmentFile(bam, "rb")
chromosomes = testFile.getChromosomes()
backgroundReadFileName = outputBAMPrefix + "_backgroundReads.bam"
tcReadFileName = outputBAMPrefix + "_TCReads.bam"
backgroundReadFile = pysam.AlignmentFile(backgroundReadFileName, "wb", template=samFile)
tcReadFile = pysam.AlignmentFile(tcReadFileName, "wb", template=samFile)
tcReadDict = dict()
for chromosome in chromosomes:
readIterator = testFile.readsInChromosome(chromosome, minBaseQual, conversionThreshold)
for read in readIterator:
if (read.isTcRead) :
tcReadDict[read.name] = 0
for read in samFile.fetch():
if read.query_name in tcReadDict:
tcReadFile.write(read)
else:
backgroundReadFile.write(read)
backgroundReadFile.close()
tcReadFile.close()
pysamIndex(backgroundReadFileName)
pysamIndex(tcReadFileName)
def Dedup(inputBAM, outputBAM, tcMutations, log, printOnly=False, verbose = True, force=False):
if(printOnly or checkStep([inputBAM], [outputBAM], force)):
samfile = pysam.AlignmentFile(inputBAM, "rb")
outfile = pysam.AlignmentFile(outputBAM, "wb", template=samfile)
processedReads = 0
retainedReads = 0
prevChr = ""
prevStart = ""
duplicateBuffer = {}
for read in samfile:
flag = read.cigarstring
chr = read.reference_id
start = read.reference_start
seq = read.query_sequence
if (read.has_tag("TC")) :
tcflag = read.get_tag("TC")
else :
tcflag = 0
if (tcflag >= tcMutations) :
if (chr != prevChr or start != prevStart) :
if (prevChr != "") :
for curSeq in duplicateBuffer :
for curFlag in duplicateBuffer[curSeq]:
for readEntry in duplicateBuffer[curSeq][curFlag]:
if not readEntry.is_duplicate:
retainedReads += 1
outfile.write(readEntry)
duplicateBuffer.clear()
if not seq in duplicateBuffer:
duplicateBuffer[seq] = {}
if not flag in duplicateBuffer[seq]:
duplicateBuffer[seq][flag] = list()
if len(duplicateBuffer[seq][flag]) > 0 :
read.is_duplicate = True
duplicateBuffer[seq][flag].append(read)
prevChr = chr
prevStart = start
processedReads += 1
for seq in duplicateBuffer:
for flag in duplicateBuffer[seq] :
for readEntry in duplicateBuffer[seq][flag]:
if not readEntry.is_duplicate:
retainedReads += 1
outfile.write(readEntry)
duplicateBuffer.clear()
outfile.close()
print("Retained " + str(retainedReads) + " of " + str(processedReads) + " reads (", file=log, end = "")
print("{0:.2f}".format(float(retainedReads) / float(processedReads)),file=log,end="")
print(" compression rate)", file=log)
pysamIndex(outputBAM)
else:
print("Skipped deduplication for " + inputBAM, file=log)
def Dedup(inputBAM,
outputBAM,
tcMutations,
log,
printOnly=False,
verbose=True,
force=False):
if (printOnly or checkStep([inputBAM], [outputBAM], force)):
samfile = pysam.AlignmentFile(inputBAM, "rb")
outfile = pysam.AlignmentFile(outputBAM, "wb", template=samfile)
processedReads = 0
retainedReads = 0
prevChr = ""
prevStart = ""
duplicateBuffer = {}
for read in samfile:
flag = read.cigarstring
chr = read.reference_id
start = read.reference_start
seq = read.query_sequence
if (read.has_tag("TC")):
tcflag = read.get_tag("TC")
else:
tcflag = 0
if (tcflag >= tcMutations):
if (chr != prevChr or start != prevStart):
if (prevChr != ""):
for curSeq in duplicateBuffer:
for curFlag in duplicateBuffer[curSeq]:
for readEntry in duplicateBuffer[curSeq][
curFlag]:
if not readEntry.is_duplicate:
retainedReads += 1
outfile.write(readEntry)
duplicateBuffer.clear()
if not seq in duplicateBuffer:
duplicateBuffer[seq] = {}
if not flag in duplicateBuffer[seq]:
duplicateBuffer[seq][flag] = list()
if len(duplicateBuffer[seq][flag]) > 0:
read.is_duplicate = True
duplicateBuffer[seq][flag].append(read)
prevChr = chr
prevStart = start
processedReads += 1
for seq in duplicateBuffer:
for flag in duplicateBuffer[seq]:
for readEntry in duplicateBuffer[seq][flag]:
if not readEntry.is_duplicate:
retainedReads += 1
outfile.write(readEntry)
duplicateBuffer.clear()
outfile.close()
print("Retained " + str(retainedReads) + " of " + str(processedReads) +
" reads (",
file=log,
end="")
print("{0:.2f}".format(float(retainedReads) / float(processedReads)),
file=log,
end="")
print(" compression rate)", file=log)
pysamIndex(outputBAM)
else:
print("Skipped deduplication for " + inputBAM, file=log)
def Filter(inputBAM, outputBAM, log, bed, MQ=2, minIdentity=0.8, NM=-1, printOnly=False, verbose=True, force=False):
if(printOnly or checkStep([inputBAM], [outputBAM], force)):
mappedReads = 0
unmappedReads = 0
filteredReads = 0
mqFiltered = 0
idFiltered = 0
nmFiltered = 0
multimapper = 0
infile = pysam.AlignmentFile(inputBAM, "rb")
outfile = pysam.AlignmentFile(outputBAM, "wb", template=infile)
# Default filtering without bed
if (bed == None) :
print("#No bed-file supplied. Running default filtering on " + inputBAM + ".",file=log)
for read in infile:
if(not read.is_secondary and not read.is_supplementary):
if(read.is_unmapped):
unmappedReads += 1
else:
mappedReads += 1
if(read.is_unmapped):
continue
if(read.mapping_quality < MQ):
mqFiltered += 1
continue
if(float(read.get_tag("XI")) < minIdentity):
idFiltered += 1
continue
if(NM > -1 and int(read.get_tag("NM")) > NM):
nmFiltered += 1
continue
if(not read.is_secondary and not read.is_supplementary):
filteredReads += 1
outfile.write(read)
print("Criterion\tFiltered reads",file=log)
print("MQ < " + str(MQ) + "\t" + str(mqFiltered),file=log)
print("ID < " + str(minIdentity) + "\t" + str(idFiltered),file=log)
print("NM > " + str(NM) + "\t" + str(nmFiltered),file=log)
print("MM\t0",file=log)
else :
# Multimap retention strategy filtering when bed is supplied
random.seed(1)
print("#Bed-file supplied. Running multimap retention filtering strategy on " + inputBAM + ".",file=log)
mappedReads, unmappedReads, filteredReads, mqFiltered, idFiltered, nmFiltered, multimapper = multimapUTRRetainment (infile, outfile, bed, minIdentity, NM, log)
#mappedReads, unmappedReads, filteredReads = multimapUTRRetainment (infile, outfile, bed, minIdentity, NM, log)
# Add number of sequenced and number of mapped reads to the read group description
# Used for creating summary file
inFileBamHeader = outfile.header
if('RG' in inFileBamHeader and len(inFileBamHeader['RG']) > 0):
slamseqInfo = SlamSeqInfo()
slamseqInfo.SequencedReads = mappedReads + unmappedReads
slamseqInfo.MappedReads = mappedReads
slamseqInfo.FilteredReads = filteredReads
slamseqInfo.MQFilteredReads = mqFiltered
slamseqInfo.IdFilteredReads = idFiltered
slamseqInfo.NmFilteredReads = nmFiltered
slamseqInfo.MultimapperReads = multimapper
if (bed != None) :
slamseqInfo.AnnotationName = os.path.basename(bed)
slamseqInfo.AnnotationMD5 = md5(bed)
else :
slamseqInfo.AnnotationName = ""
slamseqInfo.AnnotationMD5 = ""
if not isinstance(inFileBamHeader, dict):
inFileBamHeader = inFileBamHeader.to_dict()
inFileBamHeader['RG'][0]['DS'] = str(slamseqInfo)
#inFileBamHeader['RG'][0]['DS'] = "{'sequenced':" + str(mappedReads + unmappedReads) + "," + "'mapped':" + str(mappedReads) + "," + "'filtered':" + str(filteredReads) + "}"
slamDunkPG = { 'ID': 'slamdunk', 'PN': 'slamdunk filter v' + __version__, 'VN': __bam_version__ }
if('PG' in inFileBamHeader):
inFileBamHeader['PG'].append(slamDunkPG)
else:
inFileBamHeader['PG'] = [ slamDunkPG ]
infile.close()
outfile.close()
# Sort afterwards
bamSort(outputBAM, log, inFileBamHeader, verbose)
pysamIndex(outputBAM)
#pysamFlagstat(outputBAM)
#runFlagstat(outputBAM, log, verbose=verbose, dry=printOnly)
else:
print("Skipped filtering for " + inputBAM, file=log)
def Filter(inputBAM,
outputBAM,
log,
bed,
MQ=2,
minIdentity=0.8,
NM=-1,
printOnly=False,
verbose=True,
force=False):
if (printOnly or checkStep([inputBAM], [outputBAM], force)):
mappedReads = 0
unmappedReads = 0
filteredReads = 0
mqFiltered = 0
idFiltered = 0
nmFiltered = 0
multimapper = 0
infile = pysam.AlignmentFile(inputBAM, "rb")
outfile = pysam.AlignmentFile(outputBAM, "wb", template=infile)
# Default filtering without bed
if (bed == None):
print("#No bed-file supplied. Running default filtering on " +
inputBAM + ".",
file=log)
for read in infile:
if (not read.is_secondary and not read.is_supplementary):
if (read.is_unmapped):
unmappedReads += 1
else:
mappedReads += 1
if (read.is_unmapped):
continue
if (read.mapping_quality < MQ):
mqFiltered += 1
continue
if (float(read.get_tag("XI")) < minIdentity):
idFiltered += 1
continue
if (NM > -1 and int(read.get_tag("NM")) > NM):
nmFiltered += 1
continue
if (not read.is_secondary and not read.is_supplementary):
filteredReads += 1
outfile.write(read)
print("Criterion\tFiltered reads", file=log)
print("MQ < " + str(MQ) + "\t" + str(mqFiltered), file=log)
print("ID < " + str(minIdentity) + "\t" + str(idFiltered),
file=log)
print("NM > " + str(NM) + "\t" + str(nmFiltered), file=log)
print("MM\t0", file=log)
else:
# Multimap retention strategy filtering when bed is supplied
random.seed(1)
print(
"#Bed-file supplied. Running multimap retention filtering strategy on "
+ inputBAM + ".",
file=log)
mappedReads, unmappedReads, filteredReads, mqFiltered, idFiltered, nmFiltered, multimapper = multimapUTRRetainment(
infile, outfile, bed, minIdentity, NM, log)
#mappedReads, unmappedReads, filteredReads = multimapUTRRetainment (infile, outfile, bed, minIdentity, NM, log)
# Add number of sequenced and number of mapped reads to the read group description
# Used for creating summary file
inFileBamHeader = outfile.header
if ('RG' in inFileBamHeader and len(inFileBamHeader['RG']) > 0):
slamseqInfo = SlamSeqInfo()
slamseqInfo.SequencedReads = mappedReads + unmappedReads
slamseqInfo.MappedReads = mappedReads
slamseqInfo.FilteredReads = filteredReads
slamseqInfo.MQFilteredReads = mqFiltered
slamseqInfo.IdFilteredReads = idFiltered
slamseqInfo.NmFilteredReads = nmFiltered
slamseqInfo.MultimapperReads = multimapper
if (bed != None):
slamseqInfo.AnnotationName = os.path.basename(bed)
slamseqInfo.AnnotationMD5 = md5(bed)
else:
slamseqInfo.AnnotationName = ""
slamseqInfo.AnnotationMD5 = ""
if not isinstance(inFileBamHeader, dict):
inFileBamHeader = inFileBamHeader.to_dict()
inFileBamHeader['RG'][0]['DS'] = str(slamseqInfo)
#inFileBamHeader['RG'][0]['DS'] = "{'sequenced':" + str(mappedReads + unmappedReads) + "," + "'mapped':" + str(mappedReads) + "," + "'filtered':" + str(filteredReads) + "}"
slamDunkPG = {
'ID': 'slamdunk',
'PN': 'slamdunk filter v' + __version__,
'VN': __bam_version__
}
if ('PG' in inFileBamHeader):
inFileBamHeader['PG'].append(slamDunkPG)
else:
inFileBamHeader['PG'] = [slamDunkPG]
infile.close()
outfile.close()
# Sort afterwards
bamSort(outputBAM, log, inFileBamHeader, verbose)
pysamIndex(outputBAM)
#pysamFlagstat(outputBAM)
#runFlagstat(outputBAM, log, verbose=verbose, dry=printOnly)
else:
print("Skipped filtering for " + inputBAM, file=log)
def Filter(inputBAM,
outputBAM,
log,
bed,
MQ=2,
minIdentity=0.8,
NM=-1,
printOnly=False,
verbose=True,
force=False,
paired=False):
inputBAM = os.path.expanduser(inputBAM)
outputBAM = os.path.expanduser(outputBAM)
if printOnly or checkStep([inputBAM], [outputBAM], force):
(mappedReads, unmappedReads, filteredReads, mqFiltered, idFiltered,
nmFiltered, multimapper) = 0, 0, 0, 0, 0, 0, 0
infile = pysam.AlignmentFile(inputBAM, "rb")
outfile = pysam.AlignmentFile(outputBAM, "wb", template=infile)
# Default filtering without bed
if bed is None:
print("#No bed-file supplied. Running default filtering on " +
inputBAM + ".",
file=log)
if paired:
read1 = None
read2 = None
for read in infile:
if paired:
if not read.is_paired or read.mate_is_unmapped or read.is_duplicate:
unmappedReads += 1
continue
if read.is_read2:
read2 = read
else:
read1 = read
read2 = None
continue
if not read.is_secondary and not read.is_supplementary:
if read.is_unmapped:
unmappedReads += 1
continue
else:
mappedReads += 1
if not paired:
if read.mapping_quality < MQ:
mqFiltered += 1
continue
if float(read.get_tag("XI")) < minIdentity:
idFiltered += 1
continue
if -1 < NM < int(read.get_tag("NM")):
nmFiltered += 1
continue
filteredReads += 1
outfile.write(read)
else:
if read1 is None or read2 is None:
continue
if read1.query_name != read2.query_name:
continue
if read1.mapping_quality < MQ and read2.mapping_quality < MQ:
mqFiltered += 1
continue
if float(read1.get_tag("XI")) < minIdentity and float(
read2.get_tag("XI")) < minIdentity:
idFiltered += 1
continue
if -1 < NM < int(read1.get_tag("NM")) and -1 < NM < int(
read2.get_tag("NM")):
nmFiltered += 1
continue
filteredReads += 1
outfile.write(read1)
outfile.write(read2)
print("Criterion\tFiltered reads", file=log)
print("MQ < 0\t0", file=log)
print("ID < %s\t%s" % (minIdentity, idFiltered), file=log)
print("NM > %s\t%s" % (NM, nmFiltered), file=log)
print("MM\t0", file=log)
else:
# Multimap retention strategy filtering when bed is supplied
print(
"#Bed-file supplied. Running multimap retention filtering strategy on "
+ inputBAM + ".",
file=log)
(mappedReads, unmappedReads, filteredReads, mqFiltered, idFiltered,
nmFiltered,
multimapper) = multimapUTRRetainment(infile, outfile, bed,
minIdentity, NM, MQ, log)
# Add number of sequenced and number of mapped reads to the read group description
# Used for creating summary file
inFileBamHeader = outfile.header
if "RG" in inFileBamHeader and len(inFileBamHeader["RG"]) > 0:
slamseqInfo = SlamSeqInfo()
slamseqInfo.SequencedReads = mappedReads + unmappedReads
slamseqInfo.MappedReads = mappedReads
slamseqInfo.FilteredReads = filteredReads
slamseqInfo.MQFilteredReads = mqFiltered
slamseqInfo.IdFilteredReads = idFiltered
slamseqInfo.NmFilteredReads = nmFiltered
slamseqInfo.MultimapperReads = multimapper
if bed:
slamseqInfo.AnnotationName = os.path.basename(bed)
slamseqInfo.AnnotationMD5 = md5(bed)
else:
slamseqInfo.AnnotationName = ""
slamseqInfo.AnnotationMD5 = ""
if not isinstance(inFileBamHeader, dict):
inFileBamHeader = inFileBamHeader.to_dict()
inFileBamHeader["RG"][0]["DS"] = str(slamseqInfo)
slamDunkPG = {
"ID": "slamdunk",
"PN": "slamdunk filter v" + __version__,
"VN": __bam_version__
}
if "PG" in inFileBamHeader:
inFileBamHeader["PG"].append(slamDunkPG)
else:
inFileBamHeader["PG"] = [slamDunkPG]
infile.close()
outfile.close()
# Sort afterwards
bamSort(outputBAM, log, inFileBamHeader, paired=False, verbose=verbose)
if not paired:
pysamIndex(outputBAM)
else:
print("Skipped filtering for " + inputBAM, file=log)
