def bamparse((strain, target, bamfile)):
"""Parses bam files using pysam stats"""
global parsedict
# Use the stat_baseq_ext (extended base quality statistics) function of pysam stats to return records parsed
# from sorted bam files
for rec in pysamstats.stat_baseq_ext(alignmentfile=bamfile, fafile=target):
# Values of interest can be retrieved using the appropriate keys
# Simple filtering statement: if the number of matches at a particular position in the reference sequence is
# greater than the number of mismatches, and the total depth is 5 or more, add the position of the results
if rec['matches'] > rec['mismatches'] and rec['reads_all'] > 4:
# Populate the dictionary with the appropriate values
parsedict[strain][target][rec['chrom']][float(rec['pos'])][rec['reads_all']] = rec['rms_baseq']
dotter()
return parsedict
def bamparse((strain, target, bamfile)):
"""Parses bam files using pysam stats"""
global parsedict
# Use the stat_baseq_ext (extended base quality statistics) function of pysam stats to return records parsed
# from sorted bam files
for rec in pysamstats.stat_baseq_ext(alignmentfile=bamfile, fafile=target):
# Values of interest can be retrieved using the appropriate keys
# Simple filtering statement: if the number of matches at a particular position in the reference sequence is
# greater than the number of mismatches, and the total depth is 5 or more, add the position of the results
if rec['matches'] > rec['mismatches'] and rec['reads_all'] > 4:
# Populate the dictionary with the appropriate values
parsedict[strain][target][rec['chrom']][float(rec['pos'])][rec['reads_all']] = rec['rms_baseq']
dotter()
return parsedict
def _bowtie(self, raw, db):
version = Popen(['samtools', '--version'], stdout=PIPE, stderr=STDOUT).stdout.read().split('\n')[0].split()[1]
raw = map(os.path.abspath, raw)
if len(raw) == 2:
name = lcs(*raw)
indict = dict(("m" + str(x), fastq) for x, fastq in enumerate(raw, 1))
else:
indict = dict(("U", ",".join(raw)))
name = os.path.splitext(raw)[0]
# SAMtools sort v1.3 has different run parameters
workingdir = name + "tmp"
make_path(workingdir)
name += ".sorted.bam"
if version < "1.3":
samsort = SamtoolsSortCommandline(input_bam="-", out_prefix=name)
else:
samsort = SamtoolsSortCommandline(input_bam=name, o=True, out_prefix="-")
indict.update(dict(samtools=[SamtoolsViewCommandline(b=True, S=True, input_file="-"), samsort]))
if not os.path.isfile(name):
Bowtie2CommandLine(bt2=os.path.splitext(os.path.abspath(db))[0],
threads=self.threads,
very_sensitive_local=True,
a=True,
**indict)(cwd=workingdir)
if not os.path.isfile(name + ".bai"):
SamtoolsIndexCommandline(input_bam=name)(cwd=workingdir)
os.rmdir(workingdir)
genes = dict()
for rec in pysamstats.stat_baseq_ext(alignmentfile=name, fafile=db):
# Values of interest can be retrieved using the appropriate keys
# Simple filtering statement: if the number of matches at a particular position in the reference sequence is
# greater than the number of mismatches, and the total depth is 5 or more, add the position of the results
if rec['chrom'] not in genes:
genes[rec['chrom']] = dict(identity=1.0, depth=float(rec['reads_all']), quality=0.0)
else:
genes[rec['chrom']]['identity'] += 1.0
genes[rec['chrom']]['depth'] += float(rec['reads_all'])
genes[rec['chrom']]['quality'] += float(rec['rms_baseq'])
return genes
def run_pysamstats_baseq(bamFile, refFile, baseq, mapq, sampleName, record):
bam_to_process = pysam.AlignmentFile(bamFile)
keyorder = [
'Tumor_Sample_Barcode', 'chrom', 'pos', 'ref', 'alt', 'reads_all',
'reads_fwd', 'reads_rev', 'reads_pp', 'reads_pp_fwd', 'reads_pp_rev',
'matches', 'matches_fwd', 'matches_rev', 'matches_pp',
'matches_pp_fwd', 'matches_pp_rev', 'mismatches', 'mismatches_fwd',
'mismatches_rev', 'mismatches_pp', 'mismatches_pp_fwd',
'mismatches_pp_rev', 'rms_baseq', 'rms_baseq_fwd', 'rms_baseq_rev',
'rms_baseq_pp', 'rms_baseq_pp_fwd', 'rms_baseq_pp_rev',
'rms_baseq_matches', 'rms_baseq_matches_fwd', 'rms_baseq_matches_rev',
'rms_baseq_matches_pp', 'rms_baseq_matches_pp_fwd',
'rms_baseq_matches_pp_rev', 'rms_baseq_mismatches',
'rms_baseq_mismatches_fwd', 'rms_baseq_mismatches_rev',
'rms_baseq_mismatches_pp', 'rms_baseq_mismatches_pp_fwd',
'rms_baseq_mismatches_pp_rev'
]
chromosome = record.CHROM
position = record.POS
ref = record.REF
alt = record.ALT[0]
for rec in pysamstats.stat_baseq_ext(bam_to_process,
refFile,
chrom=chromosome,
start=position,
end=None,
min_mapq=mapq,
min_baseq=baseq,
no_del=False,
no_dup=True,
one_based=True,
truncate=True):
rec['alt'] = alt
rec['pos'] = position
rec['Tumor_Sample_Barcode'] = sampleName
rec = collections.OrderedDict(
sorted(rec.items(), key=lambda i: keyorder.index(i[0])))
# print "Org:",chromosome,position,ref,alt,rec['chrom'],rec['pos'],rec['ref'],"\n"
return (rec)