vcfn,qd,gq,chi2crit = sys.argv[1:]
outbase = os.path.splitext(vcfn)[0]
cut_fn = lambda sd: sd.has_key('QD') and float(sd['QD']) >= float(qd) and len(sd['indiv_gt']) >= min_indiv and sd['fh'] < fh
print >> sys.stderr, 'loading vcf',vcfn
vcf = variant_detection.load_vcf(vcfn,cutoff_fn=cut_fn,indiv_gt_phred_cut=float(gq))
print >> sys.stderr, 'convert to pm/gt matrices'
pm,gt = extract_genotypes_from_mclgr.genotypes_from_vcf_obj(vcf)
parents_prefixes = dict(zip(['A', 'B'],parent_str.split(',')))
parents = dict([(l,[k for k in gt.keys() if k.startswith(p)]) for l,p in parents_prefixes.items()])
polarized_loci,polarized_geno = extract_genotypes_from_mclgr.genotypes_by_parent(dict([(k,v) for k,v in pm.items() if int(k.split('.')[1]) < site_before]),gt,parents,remove_targets=reduce(lambda x,y: x+y,parents.values()))
print >> sys.stderr, 'filter X linked, chi2 critical %s' % chi2crit
xsites,autsites = extract_genotypes_from_mclgr.filter_Xlinked_loci(polarized_loci, polarized_geno,float(chi2crit))
print >> sys.stderr, '%s X linked, %s autosomal' % (len(xsites),len(autsites))
print >> sys.stderr, 'write output'
ret = extract_genotypes_from_mclgr.output_cross_radtag_genotypes(xsites,polarized_geno,'%s_QD%s-GQ%s_%sbp_Xchi%s.csv' % (outbase,qd,gq,site_before,chi2crit))
ret = extract_genotypes_from_mclgr.output_cross_radtag_genotypes(autsites,polarized_geno,'%s_QD%s-GQ%s_%sbp_autchi%s.csv' % (outbase,qd,gq,site_before,chi2crit))
print >> sys.stderr, 'wrote:'
print >> sys.stderr, '%s_QD%s-GQ%s_%sbp_Xchi%s.csv' % (outbase,qd,gq,site_before,chi2crit)
print >> sys.stderr, '%s_QD%s-GQ%s_%sbp_autchi%s.csv' % (outbase,qd,gq,site_before,chi2crit)
print >> sys.stderr, 'done'
AA_ind = [k for k,v in geno.items() if v.get(loc,'') == 'AA']
AA_gt = set([vcf_loc['indiv_gt'][ind]['GT'] for ind in AA_ind if ind in vcf_loc['indiv_gt'].keys()])
#BB_ind = [k for k,v in geno.items() if v.get(loc,'') == 'BB']
#BB_gt = set([vcf_loc['indiv_gt'][ind]['GT'] for ind in BB_ind if ind in vcf_loc['indiv_gt'].keys()])
if len(AA_gt) != 1: #or len(BB_gt) != 1:
AA_ctd = Util.countdict([vcf_loc['indiv_gt'][ind]['GT'] for ind in AA_ind if ind in vcf_loc['indiv_gt']])
if len(AA_ctd) == 2 and min(AA_ctd.values()) == 1:
print >> sys.stderr, 'ignoring 1 invalid AA genotype from vcf'
else:
print >> sys.stderr, '%s invalid homozygotes (AA: %s) ' % (loc,AA_ctd)
continue
AA_gt = list(AA_gt)[0]
#BB_gt = list(BB_gt)[0]
A = set(AA_gt.split('/'))
#B = set(BB_gt.split('/'))
if len(A) != 1: #or len(B) != 1:
print >> sys.stderr, '%s invalid allele mapping (A: %s B: %s)' % (loc,A,B)
continue
A = list(A)[0]
#B = list(B)[0]
B = int(A) and '0' or '1'
allele_map[loc] = {A:'A',B:'B'}
#print >> sys.stderr, '%s %s' % (loc,allele_map[loc])
if len(allele_map) == 0:
raise ValueError, 'no loci to load!'
print >> sys.stderr, 'load %s loci from %s' % (len(allele_map), new_vcf_f)
new_geno = load_vcf(new_vcf_f,allele_map,gq,return_map=True)
#print >> sys.stderr, new_geno
extract_genotypes_from_mclgr.output_cross_radtag_genotypes(loci, new_geno, sys.stdout)
for m in maps:
if ',' in m:
mapf,mIDf = m.split(',')
else:
mapf = m
mIDf = None
maploci,genotypes = extract_genotypes_from_mclgr.load_cross_radtag_genotypes(mapf,mIDf)
#print >> sys.stderr, m,'\n',[(k,len(v)) for k,v in genotypes.items()]
all_maploci.update(increment_lg(maploci,increment))
for k,v in genotypes.items():
all_genotypes[k].update(v)
increment = max([v[0] for v in all_maploci.values()])
return all_maploci,all_genotypes
if __name__ == '__main__':
out_to = sys.argv[1]
if out_to == '-':
outfh = sys.stdout
else:
outfh = open(out_to,'w')
maps = sys.argv[2:]
all_maploci,all_genotypes = merge_maps(maps)
extract_genotypes_from_mclgr.output_cross_radtag_genotypes(all_maploci,all_genotypes,outfh)
vcf_loc['indiv_gt'][ind]['GT'] for ind in AA_ind
if ind in vcf_loc['indiv_gt']
])
if len(AA_ctd) == 2 and min(AA_ctd.values()) == 1:
print >> sys.stderr, 'ignoring 1 invalid AA genotype from vcf'
else:
print >> sys.stderr, '%s invalid homozygotes (AA: %s) ' % (loc,
AA_ctd)
continue
AA_gt = list(AA_gt)[0]
#BB_gt = list(BB_gt)[0]
A = set(AA_gt.split('/'))
#B = set(BB_gt.split('/'))
if len(A) != 1: #or len(B) != 1:
print >> sys.stderr, '%s invalid allele mapping (A: %s B: %s)' % (loc,
A, B)
continue
A = list(A)[0]
#B = list(B)[0]
B = int(A) and '0' or '1'
allele_map[loc] = {A: 'A', B: 'B'}
#print >> sys.stderr, '%s %s' % (loc,allele_map[loc])
if len(allele_map) == 0:
raise ValueError, 'no loci to load!'
print >> sys.stderr, 'load %s loci from %s' % (len(allele_map), new_vcf_f)
new_geno = load_vcf(new_vcf_f, allele_map, gq, return_map=True)
#print >> sys.stderr, new_geno
extract_genotypes_from_mclgr.output_cross_radtag_genotypes(
loci, new_geno, sys.stdout)
else:
print >> sys.stderr, 'no matching genotypes for pheno line %s' % pd['id']
else:
print >> sys.stderr, 'no id in %s' % pd
return phenomaploci,phenomap
if __name__ == '__main__':
db,mapfile,outfile = sys.argv[1:4]
if ',' in mapfile:
mapf,mIDf = m.split(',')
else:
mapf = mapfile
mIDf = False
if ',' in db:
phenotypes = []
for db_i in db.split(','):
phenotypes.extend(preprocess_radtag_lane.get_table_as_dict(db_i,suppress_fc_check=True))
else:
phenotypes = preprocess_radtag_lane.get_table_as_dict(db,suppress_fc_check=True)
maploci,genotypes = extract_genotypes_from_mclgr.load_cross_radtag_genotypes(mapf,mIDf)
phenomaploci,phenomap = add_pheno_to_map(phenotypes,maploci,genotypes)
print >> sys.stderr, '%s pheno+map loci, %s lines' % (len(phenomaploci),len(phenomap))
og,mID = extract_genotypes_from_mclgr.output_cross_radtag_genotypes(phenomaploci,phenomap,outfile)
