def addLocusFromVCF2DB(self, db_vervet, inputFname=None, ref_ind_seq_id=None, locus_type_id=None, minDepth=0):
"""
2012-5.2
given a VCF file, find all the loci and submit them into db
"""
sys.stderr.write("Adding loci from %s into db ... "%(inputFname))
vcfFile = VCFFile(inputFname=inputFname, minDepth=minDepth)
counter = 0
previous_reported_counter = ''
for vcfRecord in vcfFile.parseIter():
chr = vcfRecord.chr
pos = vcfRecord.pos
pos = int(pos)
refBase = vcfRecord.data_row[0].get("GT")[0]
refBaseDBEntry = self.getSequenceDBEntry(db_vervet, sequence=refBase, comment=None)
altBase = vcfRecord.altBase
altBaseDBEntry = self.getSequenceDBEntry(db_vervet, sequence=altBase, comment=None)
locus = db_vervet.getLocus(chr=chr, start=pos, stop=pos, ref_seq=refBaseDBEntry, alt_seq=altBaseDBEntry, \
ref_ind_seq_id=ref_ind_seq_id, \
locus_type_id=locus_type_id)
counter += 1
if counter%500==0:
sys.stderr.write("%s%s"%('\x08'*len(previous_reported_counter), counter))
previous_reported_counter = repr(counter)
sys.stderr.write("%s%s"%(len(previous_reported_counter), counter))
sys.stderr.write(" Done.\n")
def countHomoHetCallsForEachSampleFromVCF(self, inputFname, outputFname, chromosome=None, chrLength=None, minDepth=1):
"""
2011-11-2
given a VCF file, count the number of h**o-ref, h**o-alt, het calls
"""
sys.stderr.write("Count the number of homozygous-ref/alt & het from %s .\n"%(inputFname))
vcfFile = VCFFile(inputFname=inputFname, minDepth=minDepth)
sampleID2data = {} #key is sampleID, value is a list of 3 numbers. 'NoOfHomoRef', 'NoOfHomoAlt', 'NoOfHet'
no_of_total = 0.
minStart = None
for vcfRecord in vcfFile.parseIter():
chr = vcfRecord.chr
pos = vcfRecord.pos
pos = int(pos)
refBase = vcfRecord.data_row[0].get("GT")[0]
for sample_id, sample_index in vcfFile.sample_id2index.iteritems():
if sample_id=='ref': #ignore the reference
continue
if sample_id not in sampleID2data:
sampleID2data[sample_id] = [0, 0, 0]
if not vcfRecord.data_row[sample_index]: #None for this sample
continue
callForThisSample = vcfRecord.data_row[sample_index].get('GT')
if not callForThisSample or callForThisSample=='NA':
continue
if callForThisSample[0]==refBase and callForThisSample[1]==refBase:
#homozygous reference allele
sampleID2data[sample_id][0]+=1
elif callForThisSample[0]==callForThisSample[1] and callForThisSample[0]!=refBase:
#homozygous alternative allele
sampleID2data[sample_id][1]+=1
elif callForThisSample[0]!=callForThisSample[1]:
sampleID2data[sample_id][2]+=1
import csv
writer = csv.writer(open(outputFname, 'w'), delimiter='\t')
writer.writerow(['#sampleID', 'chromosome', 'length', "NoOfTotal", 'NoOfHomoRef', 'NoOfHomoAlt', "FractionOfHomoAlt", 'NoOfHet', "FractionOfHet"])
sampleIDLs = sampleID2data.keys()
sampleIDLs.sort()
for sampleID in sampleIDLs:
count_data = sampleID2data.get(sampleID)
noOfHomoRef, noOfHomoAlt, noOfHet = count_data[:3]
no_of_calls = float(sum(count_data))
if no_of_calls>0:
fractionOfHomoAlt = noOfHomoAlt/no_of_calls
fractionOfHet = noOfHet/no_of_calls
else:
fractionOfHomoAlt = -1
fractionOfHet = -1
writer.writerow([sampleID, chromosome, chrLength, int(no_of_calls), noOfHomoRef, noOfHomoAlt, \
fractionOfHomoAlt, noOfHet, fractionOfHet])
del writer
sys.stderr.write("Done.\n")
def convertAlignmentReadGroup2UCLAIDInVCF(self, inputFname, outputFname, minDepth=1, includeIndels=False,\
maxContigNumber=None):
"""
2012.5.10
"""
sys.stderr.write("Converting %s from VCF to EigenStrat ...\n"%(inputFname))
vcfFile = VCFFile(inputFname=inputFname, minDepth=minDepth)
#replace Variant/PooledTissues/2002053/genome.algn.split.part17/5tissues.pooled.rmdup.bam with just monkey ID
newSampleIDHeader = []
for sampleID in vcfFile.sampleIDHeader:
readGroupData = VervetDB.VervetDB.parseAlignmentReadGroupWithoutDB(sampleID)
UCLAID = readGroupData.individual_code
newSampleIDHeader.append(UCLAID)
#new header for every output contig
newHeader = vcfFile.header[:vcfFile.sampleStartingColumn] + newSampleIDHeader
counter = 0
real_counter = 0
outVCFFile = VCFFile(outputFname=outputFname)
outVCFFile.metaInfoLs = vcfFile.metaInfoLs
outVCFFile.header = newHeader
outVCFFile.writeMetaAndHeader()
for vcfRecord in vcfFile.parseIter():
counter += 1
if not includeIndels and (len(vcfRecord.refBase)!=1 or len(vcfRecord.altBase)!=1):
#it's an indel if refBase or altBase is not just one base
continue
chr = vcfRecord.chr
if maxContigNumber:
contigNumber = int(self.contig_number_pattern.search(chr).group('contigNumber'))
if contigNumber>maxContigNumber:
continue
real_counter += 1
# set genotype whose depth is below minDepth to ./. (=missing)
for i in xrange(1, len(vcfRecord.data_row)): #[0] is the ref base
callData = vcfRecord.data_row[i]
if callData is None or callData.get('DP',0)<minDepth:
sampleColumnIndex = i+vcfFile.sampleStartingColumn-1
vcfRecord.row[sampleColumnIndex] = './.'
outVCFFile.writeVCFRecord(vcfRecord)
vcfFile.close()
#close all output files
outVCFFile.close()
sys.stderr.write("%s (out of %s) loci.\n"%(real_counter, counter))
def splitNamVCFIntoMultipleSingleChrVCF(self, inputFname, outputDir, minDepth=1, includeIndels=False, maxContigNumber=1000):
"""
2012.5.10
Two things in Nam's VCF file are to be modified.
1. extract VRC UCLAID from its sample ID
2. replace vervet1_scaffolds_Contig137 with simply "Contig137"
"""
sys.stderr.write("Converting %s from VCF to EigenStrat ...\n"%(inputFname))
from pymodule.VCFFile import VCFFile
vcfFile = VCFFile(inputFname=inputFname, minDepth=minDepth)
#replace Variant/PooledTissues/2002053/genome.algn.split.part17/5tissues.pooled.rmdup.bam with just monkey ID
import re
newSampleIDHeader = []
for sampleID in vcfFile.sampleIDHeader:
search_result = self.UCLAID_Pattern.search(sampleID)
UCLAID = search_result.group('UCLAID')
newSampleIDHeader.append(UCLAID)
#new header for every output contig
newHeader = vcfFile.header[:vcfFile.sampleStartingColumn] + newSampleIDHeader
chr2outVCFFile = {}
counter = 0
real_counter = 0
for vcfRecord in vcfFile.parseIter():
counter += 1
if not includeIndels and (len(vcfRecord.refBase)!=1 or len(vcfRecord.altBase)!=1):
#it's an indel if refBase or altBase is not just one base
continue
contig_id_pattern_result = self.contig_id_pattern.search(vcfRecord.chr)
chr = contig_id_pattern_result.group('contigID')
if maxContigNumber:
contigNumber = int(self.contig_number_pattern.search(chr).group('contigNumber'))
if contigNumber>maxContigNumber:
continue
real_counter += 1
vcfRecord.chr = chr
pos = vcfRecord.pos
if chr not in chr2outVCFFile:
outputFname = os.path.join(outputDir, '%s.vcf'%(chr))
outVCFFile = VCFFile(outputFname=outputFname)
outVCFFile.metaInfoLs = vcfFile.metaInfoLs
outVCFFile.header = newHeader
outVCFFile.writeMetaAndHeader()
chr2outVCFFile[chr] = outVCFFile
outVCFFile = chr2outVCFFile.get(chr)
# set genotype whose depth is below minDepth to ./. (=missing)
for i in xrange(1, len(vcfRecord.data_row)): #[0] is the ref base
callData = vcfRecord.data_row[i]
if callData is None or callData.get('DP',0)<minDepth:
sampleColumnIndex = i+vcfFile.sampleStartingColumn-1
vcfRecord.row[sampleColumnIndex] = './.'
outVCFFile.writeVCFRecord(vcfRecord)
vcfFile.close()
#close all output files
for chr, outVCFFile in chr2outVCFFile.iteritems():
outVCFFile.close()
sys.stderr.write("%s (out of %s) loci from %s chromosomes.\n"%(real_counter, counter, len(chr2outVCFFile)))
def replicateVCFGenotypeColumns(self, inputFname, outputFname=None, replicateIndividualTag=None, sampleID2FamilyCount=None,\
minDepth=0):
"""
2012.10.5 remove argument sampleStartingColumn
2012.5.10
VCFFile has been changed considerably and can act as a writer now.
2012.3.29
"""
sys.stderr.write("Replicating some genotype columns in %s ...\n"%(inputFname))
vcfFile = VCFFile(inputFname=inputFname, minDepth=minDepth)
outVCFFile = VCFFile(outputFname=outputFname)
outVCFFile.metaInfoLs = vcfFile.metaInfoLs
"""
outf = open(outputFname, 'w')
writer = csv.writer(outf, delimiter='\t')
#write all the headers up till the last line (which describes the samples and etc.)
for metaInfo in vcfFile.metaInfoLs:
outf.write(metaInfo)
"""
#modify the sample-id header line
sampleID2DataIndexLs = {}
oldHeader = vcfFile.header
oldHeaderLength = len(oldHeader)
newHeader = oldHeader[:vcfFile.sampleStartingColumn] #anything before the samples are same
no_of_samples = 0
for i in xrange(vcfFile.sampleStartingColumn, oldHeaderLength):
#for sample_id in vcfFile.metaInfoLs[-1][vcfFile.sampleStartingColumn:]:
sample_id = oldHeader[i].strip()
newHeader.append('%s%s%s'%(sample_id, replicateIndividualTag, 1)) #1 because it's the 1st copy
no_of_samples += 1
sampleID2DataIndexLs[sample_id] = [i] #1st copy for this sample
#add additional column headers based on each one's occurrence
extraColIndex2sampleID = {}
for sample_id, familyCount in sampleID2FamilyCount.iteritems():
for i in xrange(1, familyCount):
#if familyCount>1:
if sample_id in sampleID2DataIndexLs:
no_of_samples += 1
extraColIndex = len(newHeader)
extraColIndex2sampleID[extraColIndex] = sample_id
sampleID2DataIndexLs[sample_id].append(extraColIndex)
replicate_order = len(sampleID2DataIndexLs[sample_id])
newHeader.append("%s%s%s"%(sample_id, replicateIndividualTag, replicate_order))
outVCFFile.header = newHeader
outVCFFile.writeMetaAndHeader()
newHeaderLength = len(newHeader)
no_of_snps = 0
for vcfRecord in vcfFile.parseIter():
data_row =vcfRecord.row
#2013.09.13 replace all "./." with full NA formating i.e. "./.:.:.:.", pending fields in the "format" column
for i in xrange(vcfRecord.sampleStartingColumn, len(data_row)):
if data_row[i]=='./.': #2013.09.15 expand this NA genotype for TrioCaller
field_value_ls = []
for format_field in vcfRecord.format_column_ls:
if format_field=='GT':
field_value_ls.append('./.')
elif format_field=='PL': #for TrioCaller
field_value_ls.append('.,.,.')
else:
field_value_ls.append('.')
#field_value_ls = ['./.'] + ['.']*(len(vcfRecord.format_column_name2index)-1)
data_row[i] = ':'.join(field_value_ls)
for i in xrange(oldHeaderLength, newHeaderLength): #add more genotype copies for those extra columns
sample_id = extraColIndex2sampleID.get(i)
sourceIndex = sampleID2DataIndexLs.get(sample_id)[0]
data_row.append(data_row[sourceIndex])
outVCFFile.writer.writerow(data_row)
no_of_snps += 1
outVCFFile.close()
vcfFile.close()
sys.stderr.write("%s samples X %s SNPs.\n"%(no_of_samples, no_of_snps))
