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 extractSamples(self, db_vervet=None, inputFname=None, outputFname=None, \
tax_id_set=None, site_id_set=None, country_id_set=None, \
min_coverage=None, max_coverage=None, outputFormat=1, is_contaminated=None,\
**keywords):
"""
2013.07.03 added argument is_contaminated (whether to fetch contaminated samples or not)
2013.04.30 added argument min_coverage, max_coverage
2012.10.10
added argument outputFormat.
2012.10.5
"""
sys.stderr.write("Extracting samples from %s, %s sites & %s countries & %s taxonomies, min_coverage=%s, max_coverage=%s, outputFormat=%s, is_contaminated=%s ...\n"%\
(inputFname,\
getattr(site_id_set, '__len__', returnZeroFunc)(),\
getattr(country_id_set, '__len__', returnZeroFunc)(),\
getattr(tax_id_set, '__len__', returnZeroFunc)(), min_coverage, max_coverage,\
outputFormat, is_contaminated ))
vcfFile = VCFFile(inputFname=inputFname)
oldHeader = vcfFile.header
oldHeaderLength = len(oldHeader)
newHeader = oldHeader[:vcfFile.sampleStartingColumn] #anything before the samples are same
no_of_samples = 0
col_index2sampleID = {} #this structure stores the selected samples and their column index
for col_index, individual_name in vcfFile.get_col_index_individual_name_ls():
individualAlignment = db_vervet.parseAlignmentReadGroup(individual_name).individualAlignment
if individualAlignment is not None:
filteredAlignmentList = db_vervet.filterAlignments(alignmentLs=[individualAlignment], min_coverage=min_coverage, \
max_coverage=max_coverage, individual_site_id=None, \
sequence_filtered=None, individual_site_id_set=site_id_set, \
mask_genotype_method_id=None, parent_individual_alignment_id=None,\
country_id_set=country_id_set, tax_id_set=tax_id_set, excludeContaminant=False, \
is_contaminated=is_contaminated, excludeTissueIDSet=None,\
local_realigned=None, reduce_reads=None, report=False)
if filteredAlignmentList: #non-empty, passed the filter
newHeader.append(individual_name)
no_of_samples += 1
col_index2sampleID[col_index] = individual_name
else:
sys.stderr.write("Warning: no individualAlignment for sample %s.\n"%(individual_name))
sys.exit(3)
no_of_snps = 0
if outputFormat==1:
outVCFFile = VCFFile(outputFname=outputFname)
outVCFFile.metaInfoLs = vcfFile.metaInfoLs
outVCFFile.header = newHeader
outVCFFile.writeMetaAndHeader()
newHeaderLength = len(newHeader)
for vcfRecord in vcfFile:
data_row =vcfRecord.row[:vcfFile.sampleStartingColumn]
for i in xrange(vcfFile.sampleStartingColumn, oldHeaderLength):
if i in col_index2sampleID:
data_row.append(vcfRecord.row[i])
outVCFFile.writer.writerow(data_row)
no_of_snps += 1
outVCFFile.close()
elif outputFormat in [2,3]:
outf = open(outputFname, 'w')
if outputFormat==2:
outf.write("sampleID\n")
for col_index, sampleID in col_index2sampleID.iteritems():
outf.write("%s\n"%(sampleID))
outf.close()
vcfFile.close()
sys.stderr.write("%s samples X %s SNPs.\n"%(no_of_samples, no_of_snps))
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))
