def discoverFromVCFWithoutFilter(self, inputFname=None, outputFname=None, **keywords):
"""
2012.9.11
read minDepth from self.minDepth
2012.9.5
add minDepth=0 to VCFFile
#2012.8.20 locus_id2row_index from VCFFile is using (chr, pos) as key, not chr_pos
need a conversion in between
2012.5.8
"""
vcfFile = VCFFile(inputFname=inputFname, minDepth=self.minDepth)
vcfFile.parseFile()
read_group2col_index = vcfFile.sample_id2index
locus_id2row_index = vcfFile.locus_id2row_index
#2012.8.20 locus_id2row_index from VCFFile is using (chr, pos) as key, not chr_pos
new_locus_id2row_index = {}
for locus_id, row_index in locus_id2row_index.iteritems():
new_locus_id = '%s_%s'%(locus_id[0], locus_id[1])
new_locus_id2row_index[new_locus_id] = row_index
locus_id2row_index = new_locus_id2row_index
data_matrix = vcfFile.genotype_call_matrix
self.outputCallMatrix(data_matrix, refFastaFname=None, outputFname=outputFname, refNameSet=None, \
read_group2col_index=read_group2col_index, \
locus_id2row_index=locus_id2row_index, outputDelimiter=self.outputDelimiter)
def run(self):
"""
2012.7.13
"""
if self.debug:
import pdb
pdb.set_trace()
session = self.db_vervet.session
session.begin()
if not self.dataDir:
self.dataDir = self.db_vervet.data_dir
dataDir = self.dataDir
genotypeFile = self.db_vervet.getGenotypeFile(genotype_method_id=self.genotypeMethodID, chromosome=self.chromosome, format=self.format)
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(dataDir, genotypeFile.path)
if os.path.isfile(filename):
counter= 0
from pymodule.VCFFile import VCFFile
#allow 0 depth-> no missing data
vcfFile = VCFFile(inputFname=filename,minDepth=0)
sampleIDList = vcfFile.getSampleIDList()
writer = csv.writer(open(self.outputFname, 'w'), delimiter='\t')
sampleIDlist = ['sampleID']
columnIndexList = []
countryid_row=['country_id']
uclaIDList=['ucla_id']
speciesid_row=['tax_id']
longitudeList=['longitude'];
latitudeList=['latitude'];
for i in xrange(len(sampleIDList)):
sampleID = sampleIDList[i]
individualAlignment = self.db_vervet.parseAlignmentReadGroup(sampleID).individualAlignment
site = individualAlignment.ind_sequence.individual.site
sampleIDlist.append(sampleID)
columnIndexList.append(i)
uclaIDList.append(individualAlignment.ind_sequence.individual.ucla_id);
countryid_row.append(individualAlignment.ind_sequence.individual.site.country_id)
speciesid_row.append(individualAlignment.ind_sequence.individual.tax_id)
longitudeList.append(individualAlignment.ind_sequence.individual.longitude);
latitudeList.append(individualAlignment.ind_sequence.individual.latitude);
writer.writerow(sampleIDlist)
writer.writerow(uclaIDList)
writer.writerow(speciesid_row)
writer.writerow(countryid_row)
writer.writerow(longitudeList)
writer.writerow(latitudeList)
del writer
def selectSubPopNoDB(self,columnindexlist,ind_id_ls,vcffilename):
"""
2012.9.19
get entries of VCF-file that correspond to a sub-population with ucla_id in uclaidlist
and return genotype matrix
"""
#import pdb
filename = vcffilename
if os.path.isfile(filename):
counter= 0
from pymodule.VCFFile import VCFFile
vcfFile = VCFFile(inputFname=filename, minDepth=0)
#this is a list with the read-group names
readgroupIDList = vcfFile.getSampleIDList()
#writer = csv.writer(open(self.outputFname, 'w'), delimiter='\t')
#header = ['Chromosome', 'position', 'ref','alt']
chrom_ls=[]; ref_ls=[]; snp_pos_ls=[]; alt_ls=[]
columnIndexList = columnindexlist
datalist=[]
for vcfRecord in vcfFile:
data_row=[]
chrom_ls.append(vcfRecord.chr)
snp_pos_ls.append(vcfRecord.pos)
refBase = vcfRecord.refBase
nonRefBase = vcfRecord.altBase
ref_ls.append(refBase)
alt_ls.append(nonRefBase)
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:
if vcfCall['GT'][0]==refBase and vcfCall['GT'][1]==refBase:
gt=0
elif vcfCall['GT'][0]==refBase or vcfCall['GT'][1]==refBase:
gt=1
else:
gt=2
data_row.append(gt)
else:
data_row.append(-9)
counter += 1
datalist.append(data_row)
sys.stderr.write("%s loci in %i individuals outputted.\n"%(counter,len(columnIndexList)))
#pdb.set_trace()
data=np.array(datalist,dtype=np.float)
datastruct=hsContigDataStruct(ind_id_ls=np.array(ind_id_ls), chrom_ls=np.array(chrom_ls),ref_ls=np.array(ref_ls),snp_pos_ls=np.array(snp_pos_ls),alt_ls=np.array(alt_ls), data=data)
return datastruct
def getVCFInd(self,uclaidlist):
"""
2012.9.19
get entries of VCF-file that correspond to a sub-population with ucla_id in uclaidlist
and return genotype matrix
"""
session = self.db_vervet.session
session.begin()
if not self.dataDir:
self.dataDir = self.db_vervet.data_dir
dataDir = self.dataDir
genotypeFile = self.db_vervet.getGenotypeFile(genotype_method_id=self.genotypeMethodID, chromosome=self.chromosome, format=self.format)
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(dataDir, genotypeFile.path)
if os.path.isfile(filename):
counter= 0
from pymodule.VCFFile import VCFFile
vcfFile = VCFFile(inputFname=filename, minDepth=0)
#this is a list with the read-group names
readgroupIDList = vcfFile.getSampleIDList()
#writer = csv.writer(open(self.outputFname, 'w'), delimiter='\t')
#header = ['Chromosome', 'position', 'ref','alt']
ind_id_ls=[]; chrom_ls=[]; ref_ls=[]; snp_pos_ls=[]; alt_ls=[]
columnIndexList = []
datalist=[]
for i in xrange(len(readgroupIDList)):
readgroupID = readgroupIDList[i]
#this is the first part of the read group
individualAlignment = self.db_vervet.parseAlignmentReadGroup(readgroupID).individualAlignment
uclaid=individualAlignment.ind_sequence.individual.ucla_id
if uclaid in uclaidlist:
#header.append(readgroupID)
columnIndexList.append(i)
ind_id_ls.append(uclaid)
session.close()
return (columnIndexList,ind_id_ls)
def getLocusAndData(self, inputFname, VCFOutputType=2):
"""
2011-9-21
"""
contig_id_pattern = re.compile(r'Contig(\d+).*')
contig2locus2frequency = {}
fname = inputFname
if fname[-6:]!='vcf.gz' and fname[-3:]!='vcf':
return None
sys.stderr.write("%s ..."%fname)
contig_id_pattern_sr = contig_id_pattern.search(inputFname)
if contig_id_pattern_sr:
contig_id = contig_id_pattern_sr.group(1)
else:
contig_id = os.path.splitext(os.path.split(inputFname)[1])[0]
vcfFile = VCFFile(inputFname=self.inputFname)
counter = 0
real_counter = 0
locus_ls = []
xData_ls = []
yData_ls = []
for vcfRecord in vcfFile.parseIter():
locus_id = vcfRecord.locus_id
chr = vcfRecord.chr
pos = vcfRecord.pos
pos = int(pos)
AF1 = vcfRecord.info_tag2value.get("AF", vcfRecord.info_tag2value.get("AF1", None))
if AF1:
AF1 = float(AF1)
locus_ls.append(locus_id)
xData_ls.append(pos)
yData_ls.append(AF1)
sys.stderr.write("%s loci. Done.\n"%(len(yData_ls)))
return PassingData(contig_id=contig_id, locus_ls=locus_ls, yData_ls=yData_ls, xData_ls=xData_ls)
def createMetadataMat(self):
session = self.db_vervet.session
session.begin()
if not self.dataDir:
self.dataDir = self.db_vervet.data_dir
dataDir = self.dataDir
genotypeFile = self.db_vervet.getGenotypeFile(genotype_method_id=self.genotypeMethodID, chromosome=self.chromosome, format=self.format)
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(dataDir, genotypeFile.path)
if os.path.isfile(filename):
counter= 0
from pymodule.VCFFile import VCFFile
#allow 0 depth-> no missing data
vcfFile = VCFFile(inputFname=filename,minDepth=0)
sampleIDList = vcfFile.getSampleIDList()
sampleIDlist = ['sampleID']
columnIndexList = []
countryid_row=['country_id']
uclaIDList=['ucla_id']
speciesid_row=['tax_id']
longitudeList=['longitude'];
latitudeList=['latitude'];
for i in xrange(len(sampleIDList)):
sampleID = sampleIDList[i]
individualAlignment = self.db_vervet.parseAlignmentReadGroup(sampleID).individualAlignment
site = individualAlignment.ind_sequence.individual.site
sampleIDlist.append(sampleID)
columnIndexList.append(i)
uclaIDList.append(individualAlignment.ind_sequence.individual.ucla_id);
countryid_row.append(individualAlignment.ind_sequence.individual.site.country_id)
speciesid_row.append(individualAlignment.ind_sequence.individual.tax_id)
longitudeList.append(individualAlignment.ind_sequence.individual.longitude);
latitudeList.append(individualAlignment.ind_sequence.individual.latitude);
self.metadata=[uclaIDList,countryid_row,speciesid_row,longitudeList,latitudeList]
session.close()
def run(self):
"""
"""
if self.debug:
import pdb
pdb.set_trace()
vcfFile1 = VCFFile(inputFname=self.inputFname)
vcfFile1.parseFile()
vcfFile2 = VCFFile(inputFname=self.jnputFname)
vcfFile2.parseFile()
writer = csv.writer(open(self.outputFname, 'w'), delimiter='\t')
header = ['#chromosome', 'position', 'mismatchRate']
no_of_sites_of_input1 = len(vcfFile1.locus_id_ls)
no_of_sites_of_input2 = len(vcfFile2.locus_id_ls)
overlapping_sites_set = set(vcfFile1.locus_id_ls)&set(vcfFile2.locus_id_ls)
no_of_overlapping_sites = len(overlapping_sites_set)
no_of_total_sites = no_of_sites_of_input1+no_of_sites_of_input2-no_of_overlapping_sites
no_of_samples = len(vcfFile1.sample_id2index)
no_of_samples_in_vcf2 = len(vcfFile2.sample_id2index)
overlapping_sample_id_set = set(vcfFile1.sample_id2index.keys()) & set(vcfFile2.sample_id2index.keys())
overlapping_sample_id_list = list(overlapping_sample_id_set)
overlapping_sample_id_list.sort()
if no_of_samples!=no_of_samples_in_vcf2:
sys.stderr.write("Warning: sample size in %s is %s, in %s is %s. not matching.\n"%\
(self.inputFname, no_of_samples, self.jnputFname, no_of_samples_in_vcf2))
no_of_samples_to_compare = len(overlapping_sample_id_set)
writer.writerow(header)
locus_id2mismatchData = {}
for locus_id in overlapping_sites_set:
row_index1 = vcfFile1.locus_id2row_index[locus_id]
row_index2 = vcfFile2.locus_id2row_index[locus_id]
no_of_mismatches = 0
no_of_non_NA_pairs = 0.0
for j in xrange(len(overlapping_sample_id_list)):
sample_id = overlapping_sample_id_list[j]
col_index1 = vcfFile1.sample_id2index.get(sample_id)
col_index2 = vcfFile2.sample_id2index.get(sample_id)
call1 = vcfFile1.genotype_call_matrix[row_index1][col_index1]
call2 = vcfFile2.genotype_call_matrix[row_index2][col_index2]
if call1!='NA' and call2!='NA':
no_of_non_NA_pairs += 1
if call1!=call2:
no_of_mismatches += 1
else:
#do nothing
pass
if no_of_non_NA_pairs>0:
mismatchRate = no_of_mismatches/float(no_of_non_NA_pairs)
else:
mismatchRate = -1
locus_id2mismatchData[locus_id] = [mismatchRate, no_of_mismatches, no_of_non_NA_pairs]
counter = 0
locus_id_ls = locus_id2mismatchData.keys()
locus_id_ls.sort()
for locus_id in locus_id_ls:
mismatchData = locus_id2mismatchData.get(locus_id)
mismatchRate = mismatchData[0]
if mismatchRate<=self.maxMismatchRate:
counter += 1
chr, pos = locus_id[:2]
writer.writerow([chr, pos, mismatchRate])
sys.stderr.write("%s loci passed the maxMismatchRate out of %s overlapped loci.\n"%(counter, len(overlapping_sites_set)))
def selectSubPop(self,uclaidlist):
"""
2012.9.19
get entries of VCF-file that correspond to a sub-population with ucla_id in uclaidlist
and return genotype matrix
"""
session = self.db_vervet.session
session.begin()
if not self.dataDir:
self.dataDir = self.db_vervet.data_dir
dataDir = self.dataDir
genotypeFile = self.db_vervet.getGenotypeFile(genotype_method_id=self.genotypeMethodID, chromosome=self.chromosome, format=self.format)
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(dataDir, genotypeFile.path)
if os.path.isfile(filename):
counter= 0
from pymodule.VCFFile import VCFFile
vcfFile = VCFFile(inputFname=filename, minDepth=0)
#this is a list with the read-group names
readgroupIDList = vcfFile.getSampleIDList()
#writer = csv.writer(open(self.outputFname, 'w'), delimiter='\t')
#header = ['Chromosome', 'position', 'ref','alt']
ind_id_ls=[]; chrom_ls=[]; ref_ls=[]; snp_pos_ls=[]; alt_ls=[]
columnIndexList = []
datalist=[]
for i in xrange(len(readgroupIDList)):
readgroupID = readgroupIDList[i]
#this is the first part of the read group
individualAlignment = self.db_vervet.parseAlignmentReadGroup(readgroupID).individualAlignment
uclaid=individualAlignment.ind_sequence.individual.ucla_id
if uclaid in uclaidlist:
#header.append(readgroupID)
columnIndexList.append(i)
ind_id_ls.append(uclaid)
#writer.writerow(header)
#datalist.append(header)
for vcfRecord in vcfFile:
data_row=[]
chrom_ls.append(vcfRecord.chr)
snp_pos_ls.append(vcfRecord.pos)
refBase = vcfRecord.refBase
nonRefBase = vcfRecord.altBase
ref_ls.append(refBase)
alt_ls.append(nonRefBase)
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:
if vcfCall['GT'][0]==refBase and vcfCall['GT'][1]==refBase:
gt=0
elif vcfCall['GT'][0]==refBase or vcfCall['GT'][1]==refBase:
gt=1
else:
gt=2
data_row.append(gt)
else:
data_row.append('N')
counter += 1
datalist.append(data_row)
sys.stderr.write("%s loci in %i individuals outputted.\n"%(counter,len(columnIndexList)))
data=np.array(datalist,dtype=np.float)
datastruct=hsContigDataStruct(ind_id_ls=np.array(ind_id_ls), chrom_ls=np.array(chrom_ls),ref_ls=np.array(ref_ls),snp_pos_ls=np.array(snp_pos_ls),alt_ls=np.array(alt_ls), data=data)
session.close()
return datastruct
def run(self):
"""
2012.7.13
"""
if self.debug:
import pdb
pdb.set_trace()
session = self.db_vervet.session
session.begin()
if not self.dataDir:
self.dataDir = self.db_vervet.data_dir
dataDir = self.dataDir
genotypeFile = self.db_vervet.getGenotypeFile(genotype_method_id=self.genotypeMethodID, chromosome=self.chromosome, format=self.format)
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(dataDir, genotypeFile.path)
if os.path.isfile(filename):
counter= 0
from pymodule.VCFFile import VCFFile
#allow 0 depth-> no missing data
vcfFile = VCFFile(inputFname=filename,minDepth=0)
sampleIDList = vcfFile.getSampleIDList()
writer = csv.writer(open(self.outputFname, 'w'), delimiter='\t')
header = ['Chromosome', 'position', 'ref']
columnIndexList = []
countryid_row=['-','-','-']
speciesid_row=['-','-','-']
for i in xrange(len(sampleIDList)):
sampleID = sampleIDList[i]
individualAlignment = self.db_vervet.parseAlignmentReadGroup(sampleID).individualAlignment
site = individualAlignment.ind_sequence.individual.site
#if individualAlignment.ind_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(sampleID)
columnIndexList.append(i)
countryid_row.append(individualAlignment.ind_sequence.individual.site.country_id)
speciesid_row.append(individualAlignment.ind_sequence.individual.tax_id)
writer.writerow(header)
writer.writerow(speciesid_row)
writer.writerow(countryid_row)
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']
#if not isinstance(AF_list,types.NoneType):
# 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:
#if vcfCall['GT'][1]==refCall['GT'] and vcfCall['GT'][2]==refCall['GT']:
# gt=0
#elif vcfCall['GT'][1]==refCall['GT'] or vcfCall['GT'][2]==refCall['GT']:
# gt=0.5
data_row.append(vcfCall['GT'])
else:
data_row.append('NN')
writer.writerow(data_row)
counter += 1
sys.stderr.write("%s loci outputted.\n"%(counter))
del writer
def run(self):
"""
2012.7.13
"""
if self.debug:
import pdb
pdb.set_trace()
session = self.db_vervet.session
session.begin()
if not self.dataDir:
self.dataDir = self.db_vervet.data_dir
dataDir = self.dataDir
genotypeFile = self.db_vervet.getGenotypeFile(genotype_method_id=self.genotypeMethodID, chromosome=self.chromosome, format=self.format)
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(dataDir, genotypeFile.path)
if os.path.isfile(filename):
counter= 0
from pymodule.VCFFile import VCFFile
vcfFile = VCFFile(inputFname=filename, minDepth=0)
sampleIDList = vcfFile.getSampleIDList()
writer = csv.writer(open(self.outputFname, 'w'), delimiter='\t')
header = ['Chromosome', 'position', 'ref','alt']
columnIndexList = []
for i in xrange(len(sampleIDList)):
sampleID = sampleIDList[i]
individualAlignment = self.db_vervet.parseAlignmentReadGroup(sampleID).individualAlignment
site = individualAlignment.ind_sequence.individual.site
#if individualAlignment.ind_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(sampleID)
columnIndexList.append(i)
writer.writerow(header)
for vcfRecord in vcfFile:
data_row = [vcfRecord.chr, vcfRecord.pos]
refBase = vcfRecord.refBase
nonRefBase = vcfRecord.altBase
data_row.append(refBase)
data_row.append(nonRefBase)
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:
if vcfCall['GT'][0]==refBase and vcfCall['GT'][1]==refBase:
gt=0
elif vcfCall['GT'][0]==refBase or vcfCall['GT'][1]==refBase:
gt=1
else:
gt=2
data_row.append(gt)
else:
data_row.append('N')
writer.writerow(data_row)
counter += 1
sys.stderr.write("%s loci outputted.\n"%(counter))
del writer
def run(self):
"""
2012.7.13
"""
if self.debug:
import pdb
pdb.set_trace()
session = self.db_vervet.session
session.begin()
if not self.dataDir:
self.dataDir = self.db_vervet.data_dir
dataDir = self.dataDir
genotypeFile = self.db_vervet.getGenotypeFile(
genotype_method_id=self.genotypeMethodID, chromosome=self.chromosome, format=self.format
)
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(dataDir, genotypeFile.path)
if os.path.isfile(filename):
counter = 0
from pymodule.VCFFile import VCFFile
# allow 0 depth-> no missing data
vcfFile = VCFFile(inputFname=filename, minDepth=0)
sampleIDList = vcfFile.getSampleIDList()
writer = csv.writer(open(self.outputFname, "w"), delimiter="\t")
# header = ['Chromosome', 'position', 'ref']
columnIndexList = []
countryidList = []
speciesidList = []
keptSampleIDList = []
genotypeMat = []
for i in xrange(len(sampleIDList)):
sampleID = sampleIDList[i]
individualAlignment = self.db_vervet.parseAlignmentReadGroup(sampleID).individualAlignment
site = individualAlignment.ind_sequence.individual.site
if individualAlignment.ind_sequence.individual.target_coverage == 10:
keptSampleIDList.append(sampleID)
columnIndexList.append(i)
countryidList.append(individualAlignment.ind_sequence.individual.site.country_id)
speciesidList.append(individualAlignment.ind_sequence.individual.tax_id)
for vcfRecord in vcfFile:
data_row = []
refCall = vcfRecord.data_row[0]
# data_row.append(refCall['GT'])
# get alternative allele frequency
# AF_list = vcfRecord.info_tag2value.get('AF') #info_tag2value['AF']
# if not isinstance(AF_list,types.NoneType):
# 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:
if vcfCall["GT"][0] == refCall["GT"] and vcfCall["GT"][1] == refCall["GT"]:
gt = 0
elif vcfCall["GT"][0] == refCall["GT"] or vcfCall["GT"][1] == refCall["GT"]:
gt = 1
else:
gt = 2
data_row.append(gt)
else:
data_row.append("NN")
genotypeMat.append(data_row)
counter += 1
sys.stderr.write("%s loci outputted.\n" % (counter))
# calculate distance Matrix
import numpy as np
matArr = np.array(genotypeMat, np.int32)
distArr = np.empty((matArr.shape[1], matArr.shape[1]))
distArr[:] = np.NAN
for i in range(matArr.shape[1]):
for j in range(matArr.shape[1]):
distArr[i][j] = sum(abs(matArr[:, i] - matArr[:, j]))
# normalise so that distance is between 0 and 2:
distArr = distArr / matArr.shape[0]
np.savetxt(self.outputFname, distArr)
print countryidList
