def readVCF( filename, chrom ):
vcf = []
callablelist = []
print >>sys.stderr, "#### Loading vcf for choromosome",chrom
for line in io.BufferedReader( filez.open(filename,'r') ):
if line.startswith('#'): continue
if not line.startswith( chrom + "\t"): continue
elts = line[:-1].split('\t')
chrom, pos, id, ref, alt, qual, filt, info = elts[:8]
start, end, callable, hr = -1, -1, False, 1
for e in info.split(';'):
if e.startswith('START'): start = int(e.split('=')[1])
if e.startswith('END'): end = int(e.split('=')[1])
if e.startswith('CALLABLE'): callable = True
if e.startswith('HR') or e.startswith('TR'): hr = max(hr,int(e.split('=')[1]))
if callable:
if len(callablelist) >0 and callablelist[-1]+1 == start:
callablelist[-1] = end
else:
callablelist.append( start )
callablelist.append( end )
else:
vcf.append( Indel(int(pos),ref,alt,start,end,hr) )
print>>sys.stderr, "#### Loaded ",len(vcf)," calls"
vcf.sort()
return vcf, callablelist
def readmark( filename ):
data = {}
for line in filez.open(filename,'r'):
chrom, pos = line[:-1].split('\t')
if chrom not in data: data[chrom] = []
data[chrom].append(int(pos) - 1) # convert into 0-based coords
for chrom in data.keys():
data[chrom] = set(data[chrom])
return data
def main():
infile = sys.stdin
outfile = sys.stdout
inversion = 40
fastGT = False
v = vcf.VCF(leftalign=True, _fastGT=True)
try:
opts, args = getopt.getopt(sys.argv[1:], "ho:i:x:3F", ["help", "output", "input", "ignore"])
except:
help()
for o, a in opts:
if o in ["-h", "--help"]:
help()
sys.exit()
elif o in ["-o", "--output"]:
outfile = open(a, "w")
elif o in ["-i", "--input"]:
infile = filez.open(a, "r")
elif o == "-3":
inversion = 33
elif o == "-F":
fastGT = True
elif o in ["-x", "--ignore"]:
v.ignoreerror(a)
# process data
v.setversion(inversion)
v._fastGT = fastGT
vcfstream = v.parse(infile)
# instantiate vcfout from v, to include header and definitions.
vcfout = vcf.VCF(v)
vcfout.setversion(40)
vcfout.getinfo()["AC"] = vcf.FORMAT("AC", vcfout.NT_ALLELES, -1, "Integer", "Allele counts", -1)
vcfout.writeheader(outfile)
for data in vcfstream:
samples = v.getsamples()
ac = {}
for s in samples:
sampledata = data[s]
genotype = sampledata.get("GT", ["."])[0]
if len(genotype) == 1:
continue # haploid, or missing data
for idx in 0, 2:
if genotype[idx] == ".":
continue
ac[genotype[idx]] = ac.get(genotype[idx], 0) + 1
if len(ac.keys()) > 0:
data["info"]["AC"] = [ac.get(i, 0) for i in range(len(data["alt"]) + 1)]
vcfout.write_data(outfile, data)
def processVCF( invcf, ancvcf, ancvcf2, ancvcf3, ancvcf4, window=50 ):
invcf = filez.open(invcf,'r')
curchrom = None
for line in invcf:
# copy header
if line.startswith('#'):
# remove any existing AA definition
if line.startswith('##INFO=<ID=AA'):
continue
if removeHR:
if line.startswith('##INFO=<ID=HR'): continue
if line.startswith('##INFO=<ID=HU'): continue
if line.startswith('##INFO=<ID=TR'): continue
if line.startswith('##INFO=<ID=TU'): continue
if line.startswith('#CHROM'):
## add info fields
if reportIdx:
print '##INFO=<ID=AA, Number=1, Type=Integer, Description="Ancestral Allele (0=reference, 1=first alternative allele, etc.)">'
else:
print '##INFO=<ID=AA, Number=1, Type=String, Description="Ancestral Allele">'
if includeSZ:
print '##INFO=<ID=SZ, Number=1, Type=Integer, Description="Indel size and type (polarized if AA=0,1; with respect to reference if AA=.)">'
if findHotspot:
print "##INFO=<ID=OTHANC, Number=0, Type=Flag, Description=""Found ancestral alleles other than reference and variant; potential hotspot"">"
print "##INFO=<ID=INCANC, Number=0, Type=Flag, Description=""Found ancestral alleles inconsistent with mutation just on human lineage"">"
#print "##source=vcf-indel-polarize.py %s %s %s %s %s" % (invcf, ancvcf, ancvcf2, ancvcf3, ancvcf4)
print line[:-1]
continue
# get data
elts = line[:-1].split('\t')
chrom, pos, id, ref, altlist, qual, filt, info = (elts + [""])[:8]
pos = int(pos)
chrom = chromprefix + chrom
hr = 1
aafieldlen = 0
newinfo = []
for e in info.split(';'):
if e.startswith('HR') or e.startswith('TR'): hr = max(hr,int(e.split('=')[1]))
if e.startswith('AA'): aafieldlen = len(e)
if removeHR:
if not (e.startswith('HR') or e.startswith('TR') or e.startswith('HU') or e.startswith('TU')):
newinfo.append( e )
if removeHR:
info = ';'.join(newinfo)
# load ancestral chromosome calls if required
if curchrom != chrom:
vcf, callablelist = readVCF( ancvcf, chrom )
if ancvcf2: vcf2, callablelist2 = readVCF( ancvcf2, chrom )
if ancvcf3: vcf3, callablelist3 = readVCF( ancvcf3, chrom )
if ancvcf4: vcf4, callablelist4 = readVCF( ancvcf4, chrom )
curchrom = chrom
# make sure no biallelics
assert altlist.find(',') == -1
# do not touch SNP calls; leave any AA call in (but remove HR/TR/TU/HU if requested)
if (len(ref)==1 and len(altlist) == 1) and not snps:
print "\t".join([chrom, str(pos), id, ref, altlist, qual, filt, info] + elts[8:])
continue
# all others, remove AA call
if aafieldlen > 0:
# remove any existing AA annotation
idx = info.index('AA=')
info = info[:idx] + info[idx + aafieldlen + 1:]
# make list of alternative alleles, and loop over them
polarized = False
for idx,alt in enumerate(altlist.split(',')):
alleleidx = idx+1
ref, alt = convert(ref,alt)
typesize = len(alt)-len(ref)
if max(len(alt), len(ref)) > maxindellen:
# long deletions (or insertions); we can't deal with them, so report as AA=.
continue
if alt == "":
# <DEL> call -- report as AA=.
continue
# get calls in vicinity, find matching calls
anccalls = getVCFcalls( vcf, pos-window, pos+window )
found, other = findMatch( anccalls, pos, typesize, alt, hr )
callable = isCallable( pos, callablelist )
# do same for ancvcf2
if ancvcf2:
anccalls2 = getVCFcalls( vcf2, pos-window, pos+window )
found2, other2 = findMatch( anccalls2, pos, typesize, alt, hr )
callable2 = isCallable( pos, callablelist2 )
else:
found2 = found
callable2 = False
other2 = other
# and ancvcf3
if ancvcf3:
anccalls3 = getVCFcalls( vcf3, pos-window, pos+window )
found3, other3 = findMatch( anccalls3, pos, typesize, alt, hr )
callable3 = isCallable( pos, callablelist3 )
else:
found3 = found
callable3 = False
other3 = other
# and ancvcf4
if ancvcf4:
anccalls4 = getVCFcalls( vcf4, pos-window, pos+window )
found4, other4 = findMatch( anccalls4, pos, typesize, alt, hr )
callable4 = isCallable( pos, callablelist4 )
else:
found4 = found
callable4 = False
other4 = other
numcallable = callable + callable2 + callable3 + callable4
# get status from one of the called alleles
if callable:
found0, other0 = found, other
elif callable2:
found0, other0 = found2, other2
elif callable3:
found0, other0 = found3, other3
elif callable4:
found0, other0 = found4, other4
else:
found0, other0 = False, None
# fill in the uncallable states with one of the others
if not callable:
found, other = found0, other0
if not callable2:
found2, other2 = found0, other0
if not callable3:
found3, other3 = found0, other0
if not callable4:
found4, other4 = found0, other0
# if sufficiently many outgroups are callable, and found
# status is consistent, and no other indels were found, polarize.
if found:
sz = -typesize
if reportIdx:
aallele = alleleidx
else:
aallele = alt
else:
sz = typesize
if reportIdx:
aallele = 0
else:
aallele = ref
if numcallable >= mincallable and (found == found2) and (found == found3) and (found == found4) and \
(other == None) and (other2 == None) and (other3 == None) and (other4 == None):
if includeSZ:
info = "AA=%s;SZ=%s;%s" % (aallele, sz, info)
else:
info = "AA=%s;%s" % (aallele, info)
# done with the loop over alleles
polarized = True
break
if not polarized:
info = "AA=.;%s" % info
if numcallable >= mincallable and findHotspot:
if (other != None) or (other2 != None) or (other3 != None) or (other4 != None):
info += ";OTHANC" # other ancestral alleles than reference and variant -- hotspot!
if (found != found2) or (found != found3) or (found != found4):
info += ";INCANC" # ancestry inconsistent with mutation happening on human branch only -- hotspot, or incomplete lineage sorting
# make output
if info.endswith(";."): info = info[:-2]
print "\t".join([chrom, str(pos), id, ref, altlist, qual, filt, info] + elts[8:])
def main():
infile = sys.stdin
outfile = sys.stdout
reference = None
sample = "sample"
maxsnps = 10
maxindels = 5
maxwindow = 1000
v = vcf.VCF( _fastGT = False )
try:
opts, args = getopt.getopt(sys.argv[1:], "ho:i:r:s:n:", ["help","output=","input=","reference=","sample="])
except:
help()
raise
for o, a in opts:
if o in ["-h","--help"]:
help()
sys.exit()
elif o in ["-o","--output"]:
outfile = open(a,'w')
elif o in ["-i","--input"]:
infile = filez.open(a,'r')
elif o in ["-r","--reference"]:
reference = a
elif o in ["-s"]:
maxsnps = int(a)
elif o in ["-n"]:
maxindels = int(a)
elif o in ["--sample"]:
sample = a
if not reference:
print "Reference required"
help()
sys.exit()
# open reference
fa = pysam.Fastafile( reference )
v.setreference(fa)
# instantiate vcfout from v, to include header and definitions.
vcfout = vcf.VCF(v)
vcfout.setversion(41)
vcfout.getheader().append( ("source",' '.join(sys.argv)))
vcfout.getinfo()['RN'] = vcf.FORMAT('RN', vcfout.NT_NUMBER, 1, "String", "Name of read supporting the variant", -1)
vcfout.getfilter()['HighCallDensity'] = vcf.FORMAT('mask',vcfout.NT_NUMBER,0,"Flag","Number of indels/snps exceeding %s/%s in %s bp window" % (maxindels,maxsnps,maxwindow),".")
vcfout.setsamples( [sample] )
vcfout.writeheader( outfile )
for data in sys.stdin:
if data.startswith("#"):
continue
readname, flag, chrom, pos, mapq, cigar, mchrom, mpos, isize, seq, qual = data[:-1].split('\t')[:11]
vcflist = []
vcfdata = {'chrom':chrom, 'id':'.', 'qual':100, 'filter': ["HighCallDensity"], 'info': {'RN': [readname]}, 'format': ['GT'], sample:{'GT':["1"]}}
rpos = int(pos)-1
spos = 0
for i in re.finditer( "[0-9]*[MIDSNHP]", cigar ):
ash = i.group(0)
num = int( ash[:-1] )
if ash[-1] == 'P' or ash[-1] == 'H':
pass
elif ash[-1] == 'M':
refseq = fa.fetch(chrom,rpos,rpos+num)
for idx,c in enumerate(refseq):
c = c.upper()
if c != 'N' and seq[spos+idx] != 'N' and c != seq[spos+idx]:
# found a SNP
vcfdata['pos'] = rpos + idx
vcfdata['ref'] = c
vcfdata['alt'] = [seq[spos+idx]]
vcflist.append( vcfdata.copy() )
spos += num
rpos += num
elif ash[-1] == 'S':
spos += num
elif ash[-1] == 'I':
vcfdata['pos'] = rpos - 1
vcfdata['ref'] = fa.fetch(chrom, rpos-1, rpos)
vcfdata['alt'] = [fa.fetch(chrom, rpos-1, rpos) + seq[spos:spos+num]]
vcflist.append( vcfdata.copy() )
spos += num
elif ash[-1] == 'D':
vcfdata['pos'] = rpos - 1
vcfdata['ref'] = fa.fetch(chrom, rpos-1, rpos + num)
vcfdata['alt'] = [fa.fetch(chrom, rpos-1, rpos)]
vcflist.append( vcfdata.copy() )
rpos += num
# see if snp or indel density is too high
windowidx = 0
for idx,call in enumerate(vcflist):
while vcflist[windowidx]['pos'] < call['pos'] - maxwindow:
windowidx += 1
indels = len( [ c for c in vcflist[windowidx:idx+1] if len(c['ref']+c['alt'][0])>2 ] )
snps = len( [ c for c in vcflist[windowidx:idx+1] if len(c['ref']+c['alt'][0])==2 ] )
if indels > maxindels or snps > maxsnps:
break
else:
for call in vcflist:
call['filter'] = None
for call in vcflist:
vcfout.write_data( outfile, call )
def main():
infile = sys.stdin
outfile = sys.stdout
inversion = 40
maxn = 1e10
fastGT = False
v = vcf.VCF( leftalign=True, _fastGT=True )
try:
opts, args = getopt.getopt(sys.argv[1:], "ho:i:x:3Fm:", ["help","output","input","ignore"])
except:
help()
for o, a in opts:
if o in ["-h","--help"]:
help()
sys.exit()
elif o in ["-o","--output"]:
outfile = open(a,'w')
elif o in ["-i","--input"]:
infile = filez.open(a,'r')
elif o == "-3":
inversion = 33
elif o == "-F":
fastGT = True
elif o == "-m":
maxn = int(a)
elif o in ["-x","--ignore"]:
v.ignoreerror(a)
# process data
v.setversion(inversion)
v._fastGT = fastGT
vcfstream = v.parse( infile )
# instantiate vcfout from v, to include header and definitions.
vcfout = vcf.VCF(v)
vcfout.setversion(40)
vcfout.getinfo()['LABELS'] = vcf.FORMAT('LABELS',vcfout.NT_UNKNOWN,-1,'String','Non-hom-ref samples','')
vcfout.writeheader( outfile )
for data in vcfstream:
samples = v.getsamples()
labels = {}
for s in samples:
sampledata = data[s]
genotype = sampledata.get('GT',['.'])[0]
if len(genotype) == 1: continue # haploid, or missing data
acref = 0
for idx in 0,2:
g = genotype[idx]
if g == "." or g == 0: continue
if g not in labels: labels[g] = set()
labels[g].add( s )
report = []
for g in labels:
if 0 < len( labels[g] ) <= maxn:
report.append( "%s:%s" % (g,",".join(labels[g])) )
else:
report.append( "%s:%s" % (g,len(labels[g])) )
data['info']['LABELS'] = report
vcfout.write_data( outfile, data )
def processVCF( invcf, ancvcf, ancvcf2, ancvcf3, ancvcf4, window=50 ):
invcf = filez.open(invcf,'r')
curchrom = None
for line in invcf:
# copy header
if line.startswith('#'):
if line.startswith('#CHROM'):
## add info fields
print "##INFO=<ID=AA, Number=1, Type=String, Description=""Ancestral Allele"">"
print "##INFO=<ID=SZ, Number=1, Type=Integer, Description=""Indel size and type"">"
print "##source=vcf-indel-polarize.py %s %s %s %s %s" % (invcf, ancvcf, ancvcf2, ancvcf3, ancvcf4)
print line[:-1]
continue
# get data
elts = line[:-1].split('\t')
chrom, pos, id, ref, alt, qual, filter, info = elts[:8]
pos = int(pos)
chrom = chromprefix + chrom
ref, alt = convert(ref,alt)
typesize = len(alt)-len(ref)
if typesize != 0:
# not a snp -- adjust coordinate
pos -= vcf_offset
hr = 1
for e in info.split(';'):
if e.startswith('HR') or e.startswith('TR'): hr = max(hr,int(e.split('=')[1]))
# load ancestral chromosome calls if required
if curchrom != chrom:
vcf, callablelist = readVCF( ancvcf, chrom )
if ancvcf2: vcf2, callablelist2 = readVCF( ancvcf2, chrom )
if ancvcf3: vcf3, callablelist3 = readVCF( ancvcf3, chrom )
if ancvcf4: vcf4, callablelist4 = readVCF( ancvcf4, chrom )
curchrom = chrom
# get calls in vicinity, find matching calls
anccalls = getVCFcalls( vcf, pos-window, pos+window )
found, other = findMatch( anccalls, pos, typesize, hr )
callable = isCallable( pos, callablelist )
# do same for ancvcf2
if ancvcf2:
anccalls2 = getVCFcalls( vcf2, pos-window, pos+window )
found2, other2 = findMatch( anccalls2, pos, typesize, hr )
callable2 = isCallable( pos, callablelist2 )
else:
found2 = found
callable2 = callable
other2 = other
# and ancvcf3
if ancvcf3:
anccalls3 = getVCFcalls( vcf3, pos-window, pos+window )
found3, other3 = findMatch( anccalls3, pos, typesize, hr )
callable3 = isCallable( pos, callablelist3 )
else:
found3 = found
callable3 = callable
other3 = other
# and ancvcf4
if ancvcf4:
anccalls4 = getVCFcalls( vcf4, pos-window, pos+window )
found4, other4 = findMatch( anccalls4, pos, typesize, hr )
callable4 = isCallable( pos, callablelist4 )
else:
found4 = found
callable4 = callable
other4 = other
numcallable = callable + callable2 + callable3 + callable4
# get status from one of the called alleles
if callable:
found0, other0 = found, other
elif callable2:
found0, other0 = found2, other2
elif callable3:
found0, other0 = found3, other3
elif callable4:
found0, other0 = found4, other4
else:
found0, other0 = False, None
# fill in the uncallable states with one of the others
if not callable:
found, other = found0, other0
if not callable2:
found2, other2 = found0, other0
if not callable3:
found3, other3 = found0, other0
if not callable4:
found4, other4 = found0, other0
# if sufficiently many outgroups are callable, and found
# status is consistent, and no other indels were found, polarize.
if numcallable >= mincallable and (found == found2) and (found == found3) and (found == found4) and \
(other == None) and (other2 == None) and (other3 == None) and (other4 == None):
if found:
info = "AA=1;SZ=%s;%s" % (-typesize, info)
else:
info = "AA=0;SZ=%s;%s" % (typesize, info)
else:
info = "AA=.;SZ=%s;%s" % (typesize, info)
# make output
print "\t".join([chrom, str(pos), id, ref, alt, qual, filter, info] + elts[8:])
label = None
description = None
inversion = 40
adjust = 0 # hack, to cope with Quang's off-by-one VCFs
v = vcf.VCF()
try:
opts, args = getopt.getopt(sys.argv[1:], "ho:i:x:c:l:d:3", ["help","output","input","ignore","concordance","label","description","quang"])
except getopt.GetOptError, err:
print str(err)
help()
for o, a in opts:
if o in ["-h","--help"]:
help()
sys.exit()
elif o in ["-o","--output"]: outfile = open(a,'w')
elif o in ["-i","--input"]: infile = filez.open(a,'r')
elif o in ["-c","--concordance"]: secondaryin = filez.open(a,'r')
elif o in ["-l","--label"]: label = a
elif o in ["-d","--description"]: description = a
elif o == "-3": inversion = 33
elif o in ["-x","--ignore"]: v.ignoreerror(a)
elif o == "--quang": adjust = -1
if not description or not label or not secondaryin:
raise ValueError("Need concordance file; label; and description")
# process data
v.setversion(inversion)
secondary = vcf.VCF(v)
vcfstream = v.parse( infile )
def main():
infile = sys.stdin
outfile = sys.stdout
inversion = 40
extract = None
keepheader = False
v = vcf.VCF( _fastGT = True )
try:
opts, args = getopt.getopt(sys.argv[1:], "ho:i:x:e:3", ["help","output=","input=","ignore=","extract=","keepheader","parsegt"])
except:
help()
raise
for o, a in opts:
if o in ["-h","--help"]:
help()
sys.exit()
elif o in ["-o","--output"]:
outfile = open(a,'w')
elif o in ["-i","--input"]:
infile = filez.open(a,'r')
elif o == "-3":
inversion = 33
elif o in ["-x","--ignore"]:
print a
v.ignoreerror(a)
elif o in ["-e","--extract"]:
extract = a
elif o in ["--keepheader"]:
keepheader = True
elif o in ["--parsegt"]:
v._fastGT = False
if not extract:
print "Specification string required"
help()
sys.exit()
if extract != "*": columns = parse_extract(extract)
# process data
v.setversion(inversion)
vcfstream = v.parse( infile )
# copy vcf header
if keepheader: v.writeheader(outfile)
# deal with 'all fields'
if extract == "*": columns = allfields(v)
# write header line
outfile.write("\t".join( c[0] for c in columns ) + "\n")
for data in vcfstream:
cols = []
for e in columns:
if e[1] not in data:
raise ValueError("No column found for '%s'" % e[0])
col = data[e[1]]
if e[1] == "pos": col += 1 # use 1-based coordinates
if e[2] != None:
if e[1] == "filter":
# see if key exists in list
if e[2] in col: col = [e[2]]
else: col = ["."]
else:
# extract from dictionary
if type(col) != type({}):
print col
raise ValueError("Cannot extract '%s' from column '%s'" % (e[2],e[1]))
col = col.get(e[2],["."])
# Allow extraction from the single GT element
if e[2] == "GT": col = col[0]
if e[3] != None:
if len(col) > e[3]:
col = [col[e[3]]]
else:
col = ["."]
# format the various types
if type(col) in [type(""),type(0),type(0.0)]:
col = str(col)
elif type(col) == type({}):
if e[0] == "INFO":
col = v.format_formatdata( col, v._info, separator=";" )
else:
col = v.format_formatdata( col, v._format, key=False )
elif type(col) == type([]):
# change unextracted GT back into text format; other unextracted fields are comma-separated
if e[2] == "GT" and len(col)==3: col = ''.join(map(str,col))
elif e[1] == "ref" or e[1] == "alt": col = ','.join(map(str,col))
else: col = ":".join(map(str,col))
else:
print "Unexpected type found: ",type(col)
print "Value:",col
raise ValueError("")
cols.append(col)
print "\t".join(cols)
def main():
infile = sys.stdin
outfile = sys.stdout
inversion = 40
child = None
mingq = 0
fastGT = False
v = vcf.VCF( leftalign=True, _fastGT=True )
try:
opts, args = getopt.getopt(sys.argv[1:], "ho:i:x:3Fc:q:", ["help","output","input","ignore","child"])
except:
help()
for o, a in opts:
if o in ["-h","--help"]:
help()
sys.exit()
elif o in ["-o","--output"]:
outfile = open(a,'w')
elif o in ["-i","--input"]:
infile = filez.open(a,'r')
elif o == "-3":
inversion = 33
elif o == "-F":
fastGT = True
elif o in ["-c","--child"]:
child = a
elif o in ["-q"]:
mingq = int(a)
elif o in ["-x","--ignore"]:
v.ignoreerror(a)
# check that we have a child
if child == None: raise ValueError("Need to set child label")
# process data
v.setversion(inversion)
v._fastGT = fastGT
vcfstream = v.parse( infile )
# instantiate vcfout from v, to include header and definitions.
vcfout = vcf.VCF(v)
vcfout.setversion(40)
vcfout.getinfo()['MENDELERROR'] = vcf.FORMAT('MENDELERROR',vcfout.NT_NUMBER,0,'Flag','Non-Mendelian segregation','')
vcfout.writeheader( outfile )
for data in vcfstream:
samples = v.getsamples()
if child not in samples:
raise ValueError("Label for child (%s) not found among labels in file (%s)" % (child, ",".join(samples)))
if len(samples) != 3:
raise ValueError("Expect exactly 3 samples")
parent_gts, child_gt = [], None
gqs = []
for s in samples:
sampledata = data[s]
genotype = sampledata.get('GT',['.'])[0]
gq = sampledata.get('GQ',[0])[0]
if gq < mingq: continue # low genotype quality
if len(genotype) == 1: continue # haploid, or missing data
if genotype[0] == "." or genotype[2] == ".": continue # missing data
if s == child:
child_gt = genotype
else:
parent_gts.append(genotype)
# check for mendel error
if child_gt != None and len(parent_gts) == 2:
if ( (child_gt[0] in [parent_gts[0][0], parent_gts[0][2]] and child_gt[2] in [parent_gts[1][0], parent_gts[1][2]]) or
(child_gt[2] in [parent_gts[0][0], parent_gts[0][2]] and child_gt[0] in [parent_gts[1][0], parent_gts[1][2]]) ):
# no error
pass
else:
# check genotype qualities
data['info']['MENDELERROR'] = []
vcfout.write_data( outfile, data )
def main():
infile = sys.stdin
infile2 = None
outfile = sys.stdout
inversion = 40
outversion = 40
tandem = 4
reference = None
v = vcf.VCF( _fastGT = False )
context = 0
stranded = True
mask = False
slippage = False
indelrate = False
hotspot = False
errorrate = False
region = False
regionir = 20
transversion = False
localcalls = None
gc = 0
repwindowsize = 0
palindrome = 0
palpos = None
nohr = False
mark = None
try:
opts, args = getopt.getopt(sys.argv[1:], "ho:i:x:X:r:3mf:t:F", ["help","output=","input=","ignore=","warn=","reference=","tandem=","addcontext=","destranded","mask","filter=","slippage","gc=","indelrate","hotspot","leftalign","outversion=","region=","errorrate","repwindow=","palindrome=","transversion","localcalls=","nohr","mark=","regionir="])
except:
help()
raise
for o, a in opts:
if o in ["-h","--help"]:
help()
sys.exit()
elif o in ["-o","--output"]:
outfile = open(a,'w')
elif o in ["-i","--input"]:
infile = filez.open(a,'r')
infile2 = filez.open(a,'r') # for localcalls
elif o == "-3":
inversion = 33
elif o == "--outversion":
outversion = int(a)
elif o in ["-x","--ignore"]:
v.ignoreerror(a)
elif o in ["-X","--warn"]:
v.warnerror(a)
elif o in ["-r","--reference"]:
reference = a
elif o in ["-t","--tandem"]:
tandem = int(a)
elif o in ["-m","--mask"]:
mask = "mask"
elif o in ["-f","--filter"]:
mask = a
elif o in ["--leftalign"]:
v._leftalign = True
elif o in ["-F"]:
v._fastGT = True
elif o in ["--localcalls"]:
localcalls = map(int, a.split(','))
elif o in ["--addcontext"]:
context = int(a)
elif o in ["--destranded"]:
stranded = False
elif o in ["--slippage"]:
slippage = True
elif o in ["--errorrate"]:
errorrate = True
elif o in ["--gc"]:
gc = int(a)
elif o in ["--indelrate"]:
indelrate = True
elif o in ["--palindrome"]:
palindrome = int(a)
elif o in ["--repwindow"]:
repwindowsize = int(a)
elif o in ["--hotspot"]:
hotspot = True
elif o in ["--transversion"]:
transversion = True
elif o in ["--nohr"]:
nohr = True
elif o in ["--mark"]:
mark = a.split(',')
assert len(mark) == 3
elif o in ["--region"]:
region = True
chrom,startend = a.split(':')
start, end = map(int, startend.split('-'))
elif o in ["--regionir"]:
regionir = int(a)
if not reference:
print "Reference required"
help()
sys.exit()
if localcalls and not infile2:
print "Cannot use stdin with --localcalls"
# open reference
fa = pysam.Fastafile( reference )
if not mask: v.setreference(fa)
# annotate region
if region:
if do_palindromes:
collect_palindromes(fa, chrom, start, end, tandem, palindrome)
else:
annotate_region(fa, chrom, start, end, tandem, indelrate, regionir)
return
# read mark data
if mark: markdata = readmark( mark[0] )
# process data
v.setversion(inversion)
vcfstream = v.parse( infile , parseGenotypes=True)
if localcalls:
theLocalcalls = Localcalls( v, infile2, localcalls )
# instantiate vcfout from v, to include header and definitions.
vcfout = vcf.VCF(v)
vcfout.setversion(outversion)
vcfout.getheader().append( ("source",' '.join(["vcf-add-hr.py"]+sys.argv[1:])) )
if stranded: destranded = " (stranded)"
else: destranded = " (unstranded)"
if mask:
if mask == "mask": vcfout.getinfo()['MASK'] = vcf.FORMAT('MASK',vcfout.NT_NUMBER,1,"Character","Mask",".")
else: vcfout.getfilter()['mask'] = vcf.FORMAT('mask',vcfout.NT_NUMBER,0,"Flag","Position masked",".")
else:
if not nohr:
vcfout.getinfo()['HR'] = vcf.FORMAT('HR',vcfout.NT_NUMBER,1,"Integer","Homopolymer run length",-1)
vcfout.getinfo()['HU'] = vcf.FORMAT('HU',vcfout.NT_NUMBER,1,"String","Homopolymer run unit%s" % destranded,-1)
vcfout.getinfo()['TR'] = vcf.FORMAT('TR',vcfout.NT_NUMBER,1,"Integer","Tandem repeat run length (bp)",-1)
vcfout.getinfo()['TU'] = vcf.FORMAT('TU',vcfout.NT_NUMBER,1,"String","tandem repeat run unit%s" % destranded,-1)
if mark:
vcfout.getinfo()[ mark[1] ] = vcf.FORMAT( mark[1], vcfout.NT_NUMBER,0,"Flag", mark[2], -1)
if slippage:
vcfout.getinfo()['SL'] = vcf.FORMAT('SL',vcfout.NT_NR_ALLELES,0,"Character","Indel appears to have been caused by a polymerase slippage event",".")
vcfout.getinfo()['DR'] = vcf.FORMAT('DR',vcfout.NT_NR_ALLELES,0,"Integer","Length of direct repeat copy of long allele",-1)
if palindrome > 0:
vcfout.getinfo()['PAL'] = vcf.FORMAT('PAL',vcfout.NT_NUMBER,1,"Integer","Length of palindromic match between REF and first ALT allele",-1)
if palindrome < 0:
vcfout.getinfo()['PAL'] = vcf.FORMAT('PAL',vcfout.NT_NUMBER,1,"Integer","Length of maximum palindromic match on reference strand",-1)
if hotspot:
vcfout.getinfo()['IH'] = vcf.FORMAT('IH',vcfout.NT_NUMBER,1,"Character","Indel hotspot",".")
if transversion:
vcfout.getinfo()['TV'] = vcf.FORMAT('TV',vcfout.NT_NUMBER,1,"Integer","1 for transversions; 0 for transitions",".")
if localcalls:
vcfout.getinfo()['LC'] = vcf.FORMAT('LC',vcfout.NT_NUMBER,len(localcalls),"Integer","Number of local calls, in window(s) of size(s) %s" % ','.join(map(str,localcalls)), ".")
if repwindowsize>0:
vcfout.getinfo()['IHW'] = vcf.FORMAT('IHW',vcfout.NT_NUMBER,1,"Character","Indel hotspot in size-%s nt window" % repwindowsize, ".")
if indelrate:
vcfout.getinfo()["IR"] = vcf.FORMAT('IR',vcfout.NT_NUMBER,1,"Integer","Model-based location-specific indel rate, expressed as phred score indicating relative increase above base rate; e.g. 10=10x, 20=100x increase",-1)
if errorrate:
vcfout.getinfo()["IER"] = vcf.FORMAT('IER',vcfout.NT_NUMBER,1,"Integer","Estimated indel error rate, expressed as a Phred score of errors per read per repeat locus",-1)
if gc>0:
gclabel = 'GC'+str(gc)
vcfout.getinfo()[gclabel] = vcf.FORMAT(gclabel,vcfout.NT_NUMBER,1,"Integer","GC content fraction in %s bp windows, times 1000" % gc,".")
vcfout.writeheader( outfile )
for data in vcfstream:
chrom, pos = data['chrom'], data['pos']
snp = True
if mark:
if pos in markdata.get(chrom, []):
data['info'][ mark[1] ] = []
# for indels, skip leading base
if len(data['ref']) != 1 or sum(len(a) for a in data['alt']) != len(data['alt']):
pos += 1
snp = False
if mask:
m = fa.fetch(data['chrom'],pos,pos+1)
if mask == "mask": data['info']['MASK'] = [m]
elif m != mask: data['filter'].append('mask')
else:
if (not nohr) or errorrate or hotspot:
homopolymer, tandemlen, homopolymerunit, tandemunit, seq = get_homopolymer_and_tandem(chrom, pos, fa, tandem, stranded)
if not nohr:
data['info']['HR'] = [homopolymer]
data['info']['HU'] = [homopolymerunit]
data['info']['TR'] = [tandemlen]
data['info']['TU'] = [tandemunit]
if errorrate:
rate = get_indel_error_rate( tandemlen, tandemunit )
data['info']['IER'] = [ rate ]
if slippage:
slip = [ getslippage(seq, chrom, pos, fa, data['ref'], alt) for alt in data['alt'] ]
data['info']['SL'] = [ "NY"[sl[0]] for sl in slip ]
data['info']['DR'] = [ sl[1] for sl in slip ]
if repwindowsize>0:
category = get_repetitive_window(chrom, pos, fa, repwindowsize, tandem)
data['info']['IHW'] = [str(category)]
if palindrome!=0:
# negative window sizes signals the use of allele-independent palindromes (uses reference only)
if palindrome > 0:
pallen, palpos = get_max_palindrome(chrom, data['pos'], fa, data['ref'], data['alt'][0], palindrome)
else:
pallen, palpos = get_max_palindrome(chrom, data['pos'], fa, "", "", -palindrome)
data['info']['PAL'] = [pallen]
if transversion:
if snp:
if data['ref']+data['alt'][0] in ["AG","GA","TC","CT"]:
data['info']['TV'] = [0]
else:
data['info']['TV'] = [1]
if context!=0:
seq = fa.fetch(data['chrom'],data['pos']-abs(context),data['pos']+abs(context))
# upper-case the palindrome match positions on the reference
if palpos:
seq = seq.lower()
if palpos > -1:
posl, posr = max(0,palpos - (data['pos'] - abs(context))), min(palpos + pallen - (data['pos'] - abs(context)), len(seq))
seq = seq[:posl] + seq[posl:posr].upper() + seq[posr:]
if context>0:
data['id'] = seq[:context] + "." + seq[context:] + ":" + data['id']
else:
data['id'] = seq + ":" + data['id']
if gc>0:
ggcc = get_gc(chrom, pos, fa, gc)
data['info'][gclabel] = [ggcc]
if localcalls:
data['info']['LC'] = theLocalcalls.move( chrom, data['pos'])
if indelrate:
indelrateest = get_indelrate(chrom, pos, fa)
data['info']['IR'] = [indelrateest]
if hotspot:
cat = get_hotspot_category( homopolymer, tandemlen, tandemunit )
data['info']['IH'] = [str(cat)]
vcfout.write_data( outfile, data )
