def main():
usage = "usage: %prog [options] nrd.log.vcf\n"
parser = OptionParser(usage)
# parser.add_option("--matrixonly", action="store_true", dest="matrixonly", help="only print concordance matrixe", default=False)
# parser.add_option("--includeRef", action="store_true", dest="includeRef", help="include sites in the set ReferenceInAll", default=False)
(options, args) = parser.parse_args()
vcfilename = args[0]
basename = os.path.splitext(vcfilename)[0]
vcfobj = VcfFile(vcfilename)
vcfh = open(vcfilename, "r")
nrdallfh = open(basename + ".allgenos.nrd.txt", "w")
nrdtwofh = open(basename + ".twogenos.nrd.txt", "w")
nrdonefh = open(basename + ".onegenos.nrd.txt", "w")
vcfobj.parseMetaAndHeaderLines(vcfh)
samples = vcfobj.getSampleList()
# print samples
# print "#setname\t" + "\t".join(samples)
for vrec in vcfobj.yieldVcfRecordwithGenotypes(vcfh):
outputline = [[vrec.getPos()]]
setname = vrec.returnInfoDict()["set"] # which callset does the site belong to?
outputline.append([setname]) # we aggregate genotypes per sample heere
vrec_ziptuple = vrec.zipGenotypes(samples)
# print vrec_ziptuple
""" Since I'm testing against trio, NRD count can be 1 2 or 3
We keep track of the nrd count and print those records to the appropriate file:
nrdallfh, nrdtwofh, nrdonefh """
nrd_count = 0
for (compare, eval) in grouper(2, vrec_ziptuple):
(comp_allele1, comp_allele2) = compare[1].getAlleles()
(eval_allele1, eval_allele2) = eval[1].getAlleles()
eval_alleletype = typeofGenotype(eval_allele1, eval_allele2)
comp_alleletype = typeofGenotype(comp_allele1, comp_allele2)
if eval_alleletype == comp_alleletype:
continue
outputline.append([eval[0], str(eval_alleletype), compare[0], str(comp_alleletype)])
nrd_count += 1
output = "\t".join(melt_lol(outputline))
""" depending on the nrd count, print the records to appropirate file(s) """
if nrd_count == 3:
nrdallfh.write(output + "\n")
if nrd_count == 2:
nrdtwofh.write(output + "\n")
if nrd_count == 1:
nrdonefh.write(output + "\n")
def main():
usage = "usage: %prog [options] file.vcf.gz \n calcuate NRS and NRD on a vcf generated from CombineVariants --genotypemergeoption UNIQUIFY\n"
parser = OptionParser(usage)
parser.add_option("--matrixonly", action="store_true", dest="matrixonly", help="only print concordance matrixe", default=False)
parser.add_option("--includeRef", action="store_true", dest="includeRef", help="include sites in the set ReferenceInAll", default=False)
parser.add_option("--includeFilter", action="store_true", dest="includeFilter", help="include site filtered or not!", default=False)
(options, args)=parser.parse_args()
vcfilename=args[0]
basename=os.path.splitext(os.path.splitext(vcfilename)[0])[0]
""" row is eval, column is comparison
make a numpy matrix to represent genotype concordance matrix """
concordancetable= np.matrix( [ [ 0,0,0,0 ], [ 0,0,0,0 ], [ 0,0,0,0 ], [ 0,0,0,0 ] ] )
calledtable = np.matrix ( [ [0 ,0] , [0,0] ] )
#outputfile is the the basename of the VCF to be analyzed replaced with a variantEval.txt suffix
outputfile=".".join([basename, 'variantEval','txt'])
outputfh=open(outputfile, 'w')
#log file of sites that contribute to NRS penalty; hom-ref and no-calls at variant sites in comparison set
nrslog=".".join([basename, 'nrs','log'])
nrdlog=".".join([basename, 'nrd','log'])
filterlog=".".join([basename, 'filtered','log'])
multialleliclog=".".join([basename, 'multiallelic','log'])
concordancelog=".".join([basename, 'concordance','log'])
fieldslog=".".join([basename, 'fields', 'log'])
nrsfh=open(nrslog, 'w')
nrdfh=open(nrdlog, 'w')
filteredfh=open(filterlog, 'w')
multifh=open(multialleliclog, 'w')
concordancefh=open(concordancelog, 'w')
fieldsfh=open(fieldslog, 'w')
fieldsfh.write('set'+"\n")
vcfobj=VcfFile(vcfilename)
vcfh=gzip.open(vcfilename,'r')
vcfobj.parseMetaAndHeaderLines(vcfh)
header=vcfobj.returnHeader() +"\n"
nrsfh.write(header)
nrdfh.write(header)
filteredfh.write(header)
concordancefh.write(header)
multifh.write(header)
#outputfh.write(header)
#multifh.write(header)
samples=vcfobj.getSampleList()
#for (comparename, evalname) in grouper(2,samples):
# print comparename, evalname
vcf_sample_eval_objects = [ VcfSampleEval(compare,eval,basename) for (compare,eval) in grouper(2,samples) ]
for evalObj in vcf_sample_eval_objects:
evalObj.writeHeaders(header)
totalrecords=0
pattern=';set=(\S+)'
for vrec in vcfobj.yieldVcfRecordwithGenotypes(vcfh):
if ',' in vrec.getAlt() > 1:
outstring=vrec.toStringwithGenotypes() + "\n"
multifh.write(outstring)
#continue
""" skip homoz reference calls unless you want to include them! """
if 'ReferenceInAll' in vrec.getInfo() and options.includeRef == False:
continue
""" if variant is filtered, skip it! """
if 'filterIn' in vrec.getInfo() and options.includeFilter == False:
outstring=vrec.toStringwithGenotypes() + "\n"
filteredfh.write(outstring)
continue
if 'FilteredInAll' in vrec.getInfo():
outstring=vrec.toStringwithGenotypes() + "\n"
filteredfh.write(outstring)
continue
#returns a list [ (samplename, vcfgenotype) , ... () ]
vrec_ziptuple=vrec.zipGenotypes(samples)
""" we make a hack and make a list like so:
[(sample.variant, compare_genotype, sample.variant2, eval_genotype) ... ]
basically it halves the length of vrec_ziptuple and gives it the same structure
as the list of VcfSampleEval objects"""
compare_eval =[ compare+evalu for (compare,evalu) in grouper(2,vrec_ziptuple) ]
#what set are you in?
field=re.search(pattern, vrec.getInfo()).groups()[0]
fieldsfh.write(field+"\n")
totalrecords+=1
""" we take records two at a time, assuming the first is the comparison genotype the second is the evaluation genotype """
for (genotype_tuple, evalObj) in izip(compare_eval, vcf_sample_eval_objects):
#print genotype_tuple
compare=genotype_tuple[0:2]
eval=genotype_tuple[2::]
#print compare
#print eval
(comp_allele1, comp_allele2)=compare[1].getAlleles()
(eval_allele1, eval_allele2)=eval[1].getAlleles()
eval_alleletype=typeofGenotype(eval_allele1, eval_allele2)
comp_alleletype=typeofGenotype(comp_allele1, comp_allele2)
""" increment the cell count """
concordancetable[eval_alleletype, comp_alleletype]+=1
evalObj.incrementcellcount(eval_alleletype,comp_alleletype)
"""write gentoype record to log appropriate log file """
#print records that contirubut the NRS penalty
if eval_alleletype == 3:
if comp_alleletype == 1 or comp_alleletype==2:
outstring=vrec.toStringwithGenotypes() + "\n"
nrsfh.write( outstring)
evalObj.writeNrs(outstring)
if eval_alleletype==0:
if comp_alleletype == 1 or comp_alleletype == 2:
outstring=vrec.toStringwithGenotypes() + "\n"
nrsfh.write( outstring )
evalObj.writeNrs(outstring)
#print records that contribute to NRD penalty
if eval_alleletype==0:
if comp_alleletype == 1 or comp_alleletype == 2:
outstring=vrec.toStringwithGenotypes() + "\n"
nrdfh.write( outstring )
evalObj.writeNrd(outstring)
if comp_alleletype == 0:
outstring=vrec.toStringwithGenotypes() + "\n"
concordancefh.write( outstring )
evalObj.writeConcordance( outstring)
if eval_alleletype == 1:
if comp_alleletype == 0 or comp_alleletype == 2:
outstring=vrec.toStringwithGenotypes() + "\n"
nrdfh.write( outstring )
evalObj.writeNrd(outstring)
if comp_alleletype == 1:
outstring=vrec.toStringwithGenotypes() + "\n"
concordancefh.write( outstring )
evalObj.writeConcordance( outstring)
if eval_alleletype == 2:
if comp_alleletype == 0 or comp_alleletype ==1:
outstring=vrec.toStringwithGenotypes() + "\n"
nrdfh.write( outstring )
evalObj.writeNrd(outstring)
if comp_alleletype == 2:
outstring=vrec.toStringwithGenotypes() + "\n"
concordancefh.write( outstring )
evalObj.writeConcordance( outstring)
for evalObj in vcf_sample_eval_objects:
evalObj.writeEvalOutput()
outputfh.write("total records analyzed: " + str(totalrecords) + "\n" )
outputfh.write( "rows are eval genotypes columns comparison genotypes\n")
outputfh.write("\t".join(['','AA','AB','BB', './.' ]) +"\n")
rownames=[0,'AA', 1,'AB', 2,'BB', 3,'./.']
for (i, gt) in grouper(2,rownames):
row=concordancetable[i,:].tolist()
for r in row:
outstr="\t".join(map(str,r))
outputfh.write( gt +"\t"+outstr+"\n")
outputfh.write( "matrix sum: \n")
sum=np.sum(concordancetable)
outputfh.write( str(sum) +"\n")
#now we figure out how many sites were called or not called
calledtable[0,0]=concordancetable[0:3,0:3].sum()
calledtable[0,1]=concordancetable[0:3,3].sum()
calledtable[1,0]=concordancetable[3,0:3].sum()
calledtable[1,1]=concordancetable[3,3]
outputfh.write("\n")
rownames=[ 0,'called', 1,'./.' ]
outputfh.write( "rows are eval genotypes columns comparison genotypes\n")
outputfh.write( "\t".join(['','called','./.' ]) +"\n" )
for (i, gt) in grouper(2,rownames):
row=calledtable[i,:].tolist()
for r in row:
outstr="\t".join(map(str,r))
outputfh.write( gt +"\t"+outstr+"\n")
outputfh.write( "matrix sum: \n")
sum=np.sum(calledtable)
outputfh.write( str(sum) +"\n")
outputfh.write("\n")
if options.matrixonly == False:
discordance=concordancetable[0,1]+concordancetable[0,2]+concordancetable[1,0]+concordancetable[1,2]+concordancetable[2,0]+concordancetable[2,1]
total=concordancetable[0,1]+concordancetable[0,2]+concordancetable[1,0]+concordancetable[1,1]+ concordancetable[1,2]+concordancetable[2,0]+concordancetable[2,1] +concordancetable[2,2]
nrd=round( (float(discordance)/float(total)) * 100, 2)
variant_count_evaluation= concordancetable[1,1]+ concordancetable[1,2]+ concordancetable[2,1]+ concordancetable[2,2]
variant_count_comparison= concordancetable[0,1]+concordancetable[0,2]+concordancetable[1,1]+concordancetable[1,2]+concordancetable[2,1]+concordancetable[2,2]+concordancetable[3,1]+concordancetable[3,2]
nrs=round( float(variant_count_evaluation)/float(variant_count_comparison) * 100 , 2)
outputfh.write( "NRD: " + str(nrd) +" \n")
outputfh.write( "NRS " + str(nrs) +" \n")