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 run(self):
"""
"""
if self.debug:
import pdb
pdb.set_trace()
snpData = SNPData(input_fname=self.inputFname,
turn_into_array=1,
ignore_2nd_column=1)
snpData = SNPData.removeMonomorphicCols(snpData, NA_set=set([]))
if self.min_MAF and self.min_MAF > 0:
snpData = SNPData.removeColsByMAF(snpData,
min_MAF=self.min_MAF,
NA_set=set([]))
self.writer = VCFFile(outputFname=self.outputFname, openMode='w')
self.writer.makeupHeaderFromSampleIDList(
sampleIDList=snpData.row_id_ls)
self.writer.writeMetaAndHeader()
counter = 0
for j in xrange(len(snpData.col_id_ls)):
snp_id = snpData.col_id_ls[j]
chromosome, start = snp_id.split('_')[:2]
genotype_ls = snpData.data_matrix[:, j]
genotype_ls = utils.dict_map(number2di_nt, genotype_ls)
genotype_ls_vcf = []
alleleNucleotide2Number = {}
alleleNumber2Nucleotide = {}
for genotype in genotype_ls:
if genotype == 'NA':
genotype_ls_vcf.append("./.")
elif len(genotype) == 2:
for allele in genotype:
if allele not in alleleNucleotide2Number:
alleleNumber = len(alleleNucleotide2Number)
alleleNucleotide2Number[allele] = alleleNumber
alleleNumber2Nucleotide[alleleNumber] = allele
genotype_ls_vcf.append(
"%s/%s" % (alleleNucleotide2Number[genotype[0]],
alleleNucleotide2Number[genotype[1]]))
else:
genotype_ls_vcf.append("./.")
refAllele = alleleNumber2Nucleotide[0]
if 1 not in alleleNumber2Nucleotide:
altAllele = refAllele
else:
altAllele = alleleNumber2Nucleotide[1]
row = [
chromosome, start, ".", refAllele, altAllele, 999, 'PASS',
"DP=100", "GT"
] + genotype_ls_vcf
self.writer.writerow(row)
counter += 1
sys.stderr.write(" %s records.\n" % (counter))
self.writer.close()
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 run(self):
"""
2012.7.13
"""
if self.debug:
import pdb
pdb.set_trace()
session = self.db_vervet.session
session.begin()
if not self.data_dir:
self.data_dir = self.db_vervet.data_dir
data_dir = self.data_dir
genotypeFile = self.db_vervet.getGenotypeFile(genotype_method_id=self.genotypeMethodID, chromosome=self.chromosome, format=self.format)
#query = VervetDB.GenotypeFile.query.filter_by(genotype_method_id=self.genotypeMethodID).filter_by(format=self.format)
#for genotypeFile in query:
if not genotypeFile:
sys.stderr.write("Error: genotype_method_id %s, chromosome %s does not exist.\n"%(self.genotypeMethodID, self.chromosome))
sys.exit(2)
filename = os.path.join(data_dir, genotypeFile.path)
if os.path.isfile(filename):
counter= 0
from pymodule import VCFFile
vcfFile = VCFFile(inputFname=filename, minDepth=0)
sampleIDList = vcfFile.getSampleIDList()
writer = csv.writer(open(self.outputFname, 'w'), delimiter='\t')
header = ['Chromosome', 'position', 'ref']
columnIndexList = []
for i in xrange(len(sampleIDList)):
sampleID = sampleIDList[i]
individualAlignment = self.db_vervet.parseAlignmentReadGroup(sampleID).individualAlignment
site = individualAlignment.individual_sequence.individual.site
#2012.8.29 get scientific name from the taxonomy db
scientifcName = self.db_taxonomy.returnScientificNameGivenTaxID(individualAlignment.individual_sequence.individual.tax_id)
#if individualAlignment.individual_sequence.individual.tax_id==60711 and (site.country_id!=144 and site.country_id!=135 \
# and site.country_id!=136 and site.country_id!=148):
header.append('%s %s'%(sampleID, scientifcName))
columnIndexList.append(i)
writer.writerow(header)
for vcfRecord in vcfFile:
data_row = [vcfRecord.chr, vcfRecord.pos]
refCall = vcfRecord.data_row[0]
data_row.append(refCall['GT'])
#get alternative allele frequency
AF_list = vcfRecord.info_tag2value.get('AF') #info_tag2value['AF']
AF_list = AF_list.split(',')
AF_list = map(float, AF_list)
for columnIndex in columnIndexList:
#for vcfCall in vcfRecord.data_row[1:]: #data_row is a list of dictionary {'GT': base-call, 'DP': depth}, or None if missing.
#it includes one extra sample in index 0, which is the reference individual (from the ref column of VCF).
vcfCall = vcfRecord.data_row[columnIndex+1]
if vcfCall:
data_row.append(vcfCall['GT'])
else:
data_row.append('NA')
writer.writerow(data_row)
counter += 1
sys.stderr.write("%s loci outputted.\n"%(counter))
del writer
def outputPedigreeForPlink(self, DG=None, db_vervet=None, inputFname=None, outputFname=None, \
treatEveryOneIndependent=None, sampleIDFormat=1,\
addUngenotypedDuoParents=False):
"""
http://pngu.mgh.harvard.edu/~purcell/plink/data.shtml
either space or tab could be the delimiter.
sampleIDFormat
1: individual.ucla_id
2: input sampleID
argument addUngenotypedDuoParents
for mendel error detection, if an ungenotyped parent in a duo (the other is genotyped) is not present in the genotype file (PED/TPED/BED),
then plink won't look for its mendel inconsistency
2013.07.18
added argument addUngenotypedDuoParents
for mendel error detection, if an ungenotyped parent in a duo is not present in the genotype file (PED/TPED/BED),
then plink won't look for its mendel inconsistency
2013.06.24 added argument sampleIDFormat
1: individual.ucla_id
2: alignment.read_group
2013.1.2
copied from run()
"""
sys.stderr.write("Outputting pedigree constrained by %s to %s, treatEveryOneIndependent=%s, sampleIDFormat=%s, addUngenotypedDuoParents=%s ... "%\
(inputFname, outputFname, treatEveryOneIndependent, sampleIDFormat, addUngenotypedDuoParents))
vcfFile = VCFFile(inputFname=inputFname)
alignmentLs = []
alignmentID2sampleData = {}
individual_id2alignment = {}
for sampleID in vcfFile.getSampleIDList():
alignment = db_vervet.parseAlignmentReadGroup(sampleID).individualAlignment
alignmentLs.append(alignment)
if alignment.id in alignmentID2sampleData:
sys.stderr.write("Error: alignment %s (%s) for sample %s already in alignmentID2sampleData, with sampleID=%s.\n"%\
(alignment.id, alignment.read_group, sampleID, \
alignmentID2sampleData.get(alignment.id).sampleID))
raise
alignmentID2sampleData[alignment.id] = PassingData(sampleID=sampleID, alignment=alignment)
individual_id = alignment.individual_sequence.individual_id
if individual_id in individual_id2alignment:
sys.stderr.write("Error: alignment %s (%s) for sample %s already in alignmentID2sampleData, with sampleID=%s.\n"%\
(alignment.id, alignment.read_group, sampleID, \
alignmentID2sampleData.get(alignment.id).sampleID))
raise
individual_id2alignment[individual_id] = alignment
#alignmentLs = db_vervet.getAlignmentsFromVCFFile(inputFname =inputFname)
"""
pedigreeGraphData = db_vervet.constructPedgreeGraphOutOfAlignments(alignmentLs)
DG = pedigreeGraphData.DG
individual_id2alignmentLs = pedigreeGraphData.individual_id2alignmentLs
"""
individual_id2individual = {}
ungenotypedNodeID2Data = {}
writer = csv.writer(open(outputFname, 'w'), delimiter=' ')
counter = 0
family_id= 1 #all in one family
currentNoOfFakes = 0
for alignment in alignmentLs:
nodeID = alignment.individual_sequence.individual_id
individual = self.getIndividual(db_vervet=db_vervet, individual_id=nodeID, \
individual_id2individual=individual_id2individual)
if nodeID in DG:
parents = DG.predecessors(nodeID)
if len(parents)==2:
parent1 = self.getIndividual(db_vervet=db_vervet, individual_id=parents[0], \
individual_id2individual=individual_id2individual)
parent2 = self.getIndividual(db_vervet=db_vervet, individual_id=parents[1], \
individual_id2individual=individual_id2individual)
parent1Sex = parent1.codeSexInNumber()
parent2Sex = parent2.codeSexInNumber()
#2013.07.18 one and only genotyped, then add the ungenotyped as a ungenotyped duo
if parents[0] not in individual_id2alignment and parents[1] in individual_id2alignment:
if parents[0] not in ungenotypedNodeID2Data:
ungenotypedNodeID2Data[parents[0]] = PassingData(individualDBEntry=parent1, sex=parent1Sex)
elif parents[0] in individual_id2alignment and parents[1] not in individual_id2alignment:
if parents[1] not in ungenotypedNodeID2Data:
ungenotypedNodeID2Data[parents[1]] = PassingData(individualDBEntry=parent2, sex=parent2Sex)
if parent1Sex==2:
#swap the father and mother row
tmp = parent1
parent1 = parent2
parent2 = tmp
father_id = self.getProperSampleIDForPlinkOutput(individual=parent1, \
alignmentID2sampleData=alignmentID2sampleData, \
individual_id2alignment=individual_id2alignment, sampleIDFormat=sampleIDFormat)
mother_id = self.getProperSampleIDForPlinkOutput(individual=parent2, \
alignmentID2sampleData=alignmentID2sampleData, \
individual_id2alignment=individual_id2alignment, sampleIDFormat=sampleIDFormat)
elif len(parents)==1:
parent1 = self.getIndividual(db_vervet=db_vervet, individual_id=parents[0], \
individual_id2individual=individual_id2individual)
parent1Sex = parent1.codeSexInNumber()
if parent1Sex==2:
parent2Sex = 1
father_id = 0
mother_id = self.getProperSampleIDForPlinkOutput(individual=parent1, \
alignmentID2sampleData=alignmentID2sampleData, \
individual_id2alignment=individual_id2alignment, sampleIDFormat=sampleIDFormat)
else:
parent2Sex = 2
father_id = self.getProperSampleIDForPlinkOutput(individual=parent1, \
alignmentID2sampleData=alignmentID2sampleData, \
individual_id2alignment=individual_id2alignment, sampleIDFormat=sampleIDFormat)
mother_id = 0
#2013.07.18 parent1 (parents[0]) has to be in individual_id2alignment (genotyped) in order for the other
#to qualify as an ungenotype parent in a duo
if parents[0] in individual_id2alignment:
#if parents[0] not in ungenotypedNodeID2Data:
# ungenotypedNodeID2Data[parents[0]] = PassingData(individualDBEntry=parent1, sex=parent1Sex)
fakeParentData = self.generateFakeIndividualID(pedigreeGraph=DG, currentNoOfFakes=currentNoOfFakes)
currentNoOfFakes = fakeParentData.currentNoOfFakes
fakeParent2ID = fakeParentData.individualID
if fakeParent2ID not in individual_id2alignment:
if fakeParent2ID not in ungenotypedNodeID2Data:
ungenotypedNodeID2Data[fakeParent2ID] = PassingData(individualDBEntry=None, sex=parent2Sex)
elif len(parents)==0:
father_id = 0
mother_id = 0
else:
sys.stderr.write("Error: number of parents (%s) for %s is %s.\n"%(repr(parents), nodeID, len(parents)))
sys.exit(3)
else: # founders
father_id = 0
mother_id = 0
if treatEveryOneIndependent: #force the parents to be 0, everyone becomes founders
father_id = 0
mother_id = 0
individual_id = self.getProperSampleIDForPlinkOutput(individual=individual, \
alignmentID2sampleData=alignmentID2sampleData, \
individual_id2alignment=individual_id2alignment, sampleIDFormat=sampleIDFormat)
data_row = [family_id, individual_id, father_id, mother_id, \
individual.codeSexInNumber(), 1]
writer.writerow(data_row)
counter += 1
noOfUngenotypedParentsOutputted = 0
if addUngenotypedDuoParents:
for ungenotypedNodeID, pdata in ungenotypedNodeID2Data.iteritems():
individual_id = self.getProperSampleIDForPlinkOutput(individual=pdata.individualDBEntry, \
alignmentID2sampleData=alignmentID2sampleData, \
individual_id2alignment=individual_id2alignment, \
sampleIDFormat=sampleIDFormat, defaultSampleID=ungenotypedNodeID)
data_row = [family_id, individual_id, 0, 0, pdata.sex, 1]
writer.writerow(data_row)
noOfUngenotypedParentsOutputted += 1
sys.stderr.write("%s individuals and %s ungenotyped duo-parents outputted, number of fake parents %s, addUngenotypedDuoParents=%s.\n"%\
(counter, noOfUngenotypedParentsOutputted, currentNoOfFakes, addUngenotypedDuoParents))
del writer
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 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 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))
def run(self): """ 2011-7-11 """ if self.run_type!=1: self.needSplitChrIntervalData = False #2013.06.21 turn this off before setup_run() to not construct chr2IntervalDataLs else: self.needSplitChrIntervalData = True pdata = self.setup_run() workflow = pdata.workflow db_vervet = self.db if self.run_type in [2,3]: inputData = self.registerAllInputFiles(workflow, self.inputDir, input_site_handler=self.input_site_handler, \ checkEmptyVCFByReading=self.checkEmptyVCFByReading,\ pegasusFolderName=self.pegasusFolderName,\ maxContigID=self.maxContigID, \ minContigID=self.minContigID, db_vervet=db_vervet, \ needToKnowNoOfLoci=abs(1-self.notToKnowNoOfLoci),\ minNoOfLociInVCF=self.minNoOfLociInVCF) #ignore files with too few loci inputF = inputData.jobDataLs[0].vcfFile vcfFile = VCFFile(inputFname=inputF.abspath) alignmentLs = db_vervet.getAlignmentsFromVCFSampleIDList(vcfFile.getSampleIDList()) del vcfFile cumulativeMedianDepth = db_vervet.getCumulativeAlignmentMedianDepth(alignmentLs=pdata.alignmentLs, \ defaultSampleAlignmentDepth=self.defaultSampleAlignmentDepth) registerReferenceData = pdata.registerReferenceData if self.run_type==1: #chr2size = set(['Contig149']) #temporary when testing Contig149 #chr2size = set(['1MbBAC']) #temporary when testing the 1Mb-BAC (formerly vervet_path2) #2012.6.12 #self.outputAlignmentDepthAndOthersForFilter(db_vervet=db_vervet, outputFname=self.alnStatForFilterFname, \ # ref_ind_seq_id=self.ref_ind_seq_id, \ # foldChange=self.depthFoldChange, minGQ=30) #minGQ doesn't matter anymore. self.addGenotypeCallJobs(workflow=workflow, alignmentDataLs=pdata.alignmentDataLs, chr2IntervalDataLs=self.chr2IntervalDataLs, \ registerReferenceData=registerReferenceData, \ site_handler=self.site_handler, input_site_handler=self.input_site_handler,\ needFastaIndexJob=self.needFastaIndexJob, needFastaDictJob=self.needFastaDictJob, \ intervalSize=self.intervalSize, intervalOverlapSize=self.intervalOverlapSize, \ site_type=self.site_type, data_dir=self.data_dir,\ outputDirPrefix="",\ genotypeCallerType=self.genotypeCallerType,\ cumulativeMedianDepth=cumulativeMedianDepth,\ transferOutput=True) elif self.run_type in [2, 3]: self.addTrioCallerJobsONVCFFiles(workflow=workflow, alignmentLs=alignmentLs, inputData=inputData, \ samtools=workflow.samtools, \ genotyperJava=workflow.genotyperJava, SelectVariantsJava=workflow.SelectVariantsJava, \ GenomeAnalysisTKJar=workflow.GenomeAnalysisTKJar, \ addOrReplaceReadGroupsJava=workflow.addOrReplaceReadGroupsJava, AddOrReplaceReadGroupsJar=workflow.AddOrReplaceReadGroupsJar, \ CreateSequenceDictionaryJava=workflow.CreateSequenceDictionaryJava, CreateSequenceDictionaryJar=workflow.CreateSequenceDictionaryJar, \ MergeSamFilesJar=workflow.MergeSamFilesJar, \ BuildBamIndexFilesJava=workflow.BuildBamIndexFilesJava, BuildBamIndexJar=workflow.BuildBamIndexJar, \ mv=workflow.mv, CallVariantBySamtools=workflow.CallVariantBySamtools, \ trioCallerPath=self.trioCallerPath, trioCallerWrapper=workflow.trioCallerWrapper, \ replicateIndividualTag=self.replicateIndividualTag, treatEveryOneIndependent=self.treatEveryOneIndependent,\ bgzip_tabix=workflow.bgzip_tabix, vcf_convert=workflow.vcf_convert, \ vcf_isec=workflow.vcf_isec, vcf_concat=workflow.vcf_concat, \ concatGATK=workflow.concatGATK, concatSamtools=workflow.concatSamtools,\ ligateVcf=self.ligateVcf, ligateVcfExecutableFile=self.ligateVcfExecutableFile,\ registerReferenceData=registerReferenceData, \ namespace=workflow.namespace, version=workflow.version, site_handler=self.site_handler, input_site_handler=self.input_site_handler,\ needFastaIndexJob=self.needFastaIndexJob, needFastaDictJob=self.needFastaDictJob, \ outputDirPrefix="", \ intervalSize=self.intervalSize, intervalOverlapSize=self.intervalOverlapSize, \ site_type=self.site_type, data_dir=self.data_dir,\ onlyKeepBiAllelicSNP=self.onlyKeepBiAllelicSNP, maxSNPMissingRate=self.maxSNPMissingRate,\ alnStatForFilterF=None, cumulativeMedianDepth=cumulativeMedianDepth,\ run_type=self.run_type, transferOutput=True) self.end_run()
def run(self):
"""
2012.7.13
"""
if self.debug:
import pdb
pdb.set_trace()
session = self.db_vervet.session
session.begin()
if not self.data_dir:
self.data_dir = self.db_vervet.data_dir
data_dir = self.data_dir
realPath = os.path.realpath(self.inputFname)
logMessage = "file %s.\n"%(self.inputFname)
if NextGenSeq.isFileNameVCF(realPath, includeIndelVCF=True) and \
not NextGenSeq.isVCFFileEmpty(realPath, checkContent=self.checkEmptyVCFByReading):
vcfFile = VCFFile(inputFname=self.inputFname)
individualAlignmentLs = self.getAlignmentLsFromVCF(db_vervet=self.db_vervet, vcfFile=vcfFile)
genotypeMethod = self.db_vervet.getGenotypeMethod(short_name=self.genotypeMethodShortName, \
individualAlignmentLs=individualAlignmentLs,\
no_of_individuals=len(individualAlignmentLs), no_of_loci=None,\
data_dir=self.data_dir)
self.checkIfAlignmentListMatchMethodDBEntry(individualAlignmentLs, genotypeMethod, session)
pdata = self.getNoOfLociFromVCFFile(vcfFile)
chromosome2noOfLoci = pdata.chromosome2noOfLoci
no_of_loci = pdata.no_of_loci
if no_of_loci>0: #file with zero loci could have identical md5sum
try:
md5sum = utils.get_md5sum(realPath)
except:
sys.stderr.write('Except type: %s\n'%repr(sys.exc_info()))
import traceback
traceback.print_exc()
self.cleanUpAndExitOnFailure(exitCode=4)
else:
md5sum = None
"""
db_entry = VervetDB.GenotypeFile.query.filter_by(md5sum=md5sum).first()
if db_entry:
sys.stderr.write("Warning: another file %s with the identical md5sum %s as this file %s is already in db.\n"%\
(db_entry.path, md5sum, realPath))
session.rollback()
#2012.8.3 when the jobs are clustered into one merged job and it failed halfway
# and retried elsewhere, the redundancy check should not exit with non-zero. otherwise the merged job would fail again.
self.cleanUpAndExitOnFailure(exitCode=0)
"""
no_of_individuals = len(individualAlignmentLs)
no_of_chromosomes = len(chromosome2noOfLoci)
if no_of_chromosomes == 1: #2012.8.30 use 1st chromosome
chromosome = chromosome2noOfLoci.keys()[0]
else:
chromosome = None
genotypeFile = self.db_vervet.getGenotypeFile(genotype_method=genotypeMethod,\
chromosome=chromosome, format=self.format, path=None, file_size=None, md5sum=md5sum,\
original_path=realPath, no_of_individuals=no_of_individuals, no_of_loci=no_of_loci,\
data_dir=self.data_dir, no_of_chromosomes=no_of_chromosomes)
if genotypeFile.id and genotypeFile.path:
isPathInDB = self.db_vervet.isPathInDBAffiliatedStorage(relativePath=genotypeFile.path, data_dir=self.data_dir)
if isPathInDB==-1:
sys.stderr.write("Error while updating genotypeFile.path with the new path, %s.\n"%(genotypeFile.path))
self.cleanUpAndExitOnFailure(exitCode=isPathInDB)
elif isPathInDB==1: #successful exit, entry already in db
sys.stderr.write("Warning: file %s is already in db.\n"%\
(genotypeFile.path))
session.rollback()
self.cleanUpAndExitOnFailure(exitCode=0)
else: #not in db affiliated storage, keep going.
pass
#move the file and update the db_entry's path as well
inputFileBasename = os.path.basename(self.inputFname)
relativePath = genotypeFile.constructRelativePath(sourceFilename=inputFileBasename)
exitCode = self.db_vervet.moveFileIntoDBAffiliatedStorage(db_entry=genotypeFile, filename=inputFileBasename, \
inputDir=os.path.split(self.inputFname)[0], dstFilename=os.path.join(self.data_dir, relativePath), \
relativeOutputDir=None, shellCommand='cp -rL', \
srcFilenameLs=self.srcFilenameLs, dstFilenameLs=self.dstFilenameLs,\
constructRelativePathFunction=genotypeFile.constructRelativePath)
if exitCode!=0:
sys.stderr.write("Error: moveFileIntoDBAffiliatedStorage() exits with %s code.\n"%(exitCode))
session.rollback()
self.cleanUpAndExitOnFailure(exitCode=exitCode)
#copy the tbi (tabix) index file if it exists
tbiFilename = '%s.tbi'%(realPath)
if os.path.isfile(tbiFilename):
srcFilename = tbiFilename
dstFilename = os.path.join(self.data_dir, '%s.tbi'%(genotypeFile.path))
utils.copyFile(srcFilename=srcFilename, dstFilename=dstFilename)
logMessage += "tbi file %s has been copied to %s.\n"%(srcFilename, dstFilename)
## 2012.7.17 commented out because md5sum is calcualted above
#db_vervet.updateDBEntryMD5SUM(db_entry=genotypeFile, data_dir=data_dir)
# #2012.7.17 record the size of db_entry.path (folder or file)
self.db_vervet.updateDBEntryPathFileSize(db_entry=genotypeFile, data_dir=self.data_dir)
vcfFile.close()
logMessage += "%s individuals, %s loci, md5sum=%s.\n"%(no_of_individuals, no_of_loci, md5sum)
else:
logMessage += " is empty (no loci) or not VCF file.\n"
self.outputLogMessage(logMessage)
if self.commit:
try:
session.flush()
session.commit()
except:
sys.stderr.write('Except type: %s\n'%repr(sys.exc_info()))
import traceback
traceback.print_exc()
self.cleanUpAndExitOnFailure(exitCode=3)
else:
session.rollback()
#delete all target files but exit gracefully (exit 0)
self.cleanUpAndExitOnFailure(exitCode=0)
