def rvs_anno(chrom, pos, ref, alt):
# annotate variants with rvs, and add the emtpy records to bulk_vep
##################
# construct vkeys for rvs
all_vkeys_list = []
# dict for v_id => rvs_id
rvs_dict = {}
# get the functional arguments of v2k function
rvs_id = VarCharKey.v2k(chrom, int(pos), int(pos), alt)
all_vkeys_list.append(rvs_id)
print all_vkeys_list
all_vkeys = ','.join(all_vkeys_list)
##################
# request rvs
rvs_vars = {}
for mode in ['impact', 'prediction']:
url = 'https://rvs.u.hpc.mssm.edu/rest/{}/vkey/{}'.format(
mode, all_vkeys)
print url
r = requests.get(url, headers={"Content-Type": "application/json"})
rvs_vars[mode] = r.json()
# parse RVS record
#rvs=rvs[0]
#VAR['p_change']={'gene_id':rvs['gene_id'],'cvar':rvs['hgvs_c'],'pvar':rvs['hgvs_p'],'transcript_id':rvs['enst']}
#VAR['consequence']=rvs['effect']
#print 'NO RVS, USING CSV INFO'
#ENSG00000164256:ENST00000296682:exon11:c.2497_2580del:p.833_860del
#variant=dict()
#variant['p_change'] = {'pvar': g['RVS']['impact']['hgvs_p'], 'cvar': g['RVS']['impact']['hgvs_c'], 'gene_id': gene_id, 'transcript_id': g['RVS']['impact']['enst']}
#variant['consequence'] = [g['RVS']['impact']['effect'], {'impact': g['RVS']['impact']['impact']} ]
#if g['RVS'].get('prediction',{}): temp = g['RVS']['prediction']
#for pred in ['Polyphen2_HDIV', 'SIFT', 'CADD', 'MutationTaster', 'ensemble_prediction', 'FATHMM', 'MutationAssessor', 'phastCons', 'GWAVA_region', 'Polyphen2_HVAR']: this['consequence'][1][pred] = temp[pred]
return rvs_vars
def rvs_anno(chrom, pos, ref, alt):
# annotate variants with rvs, and add the emtpy records to bulk_vep
##################
# construct vkeys for rvs
all_vkeys_list = []
# dict for v_id => rvs_id
rvs_dict = {}
# get the functional arguments of v2k function
rvs_id=VarCharKey.v2k(chrom, int(pos), int(pos), alt)
all_vkeys_list.append(rvs_id)
print all_vkeys_list
all_vkeys = ','.join(all_vkeys_list)
##################
# request rvs
rvs_vars = {}
for mode in ['impact','prediction']:
url='https://rvs.u.hpc.mssm.edu/rest/{}/vkey/{}'.format(mode,all_vkeys)
print url
r = requests.get(url, headers={ "Content-Type" : "application/json"})
rvs_vars[mode]=r.json()
# parse RVS record
#rvs=rvs[0]
#VAR['p_change']={'gene_id':rvs['gene_id'],'cvar':rvs['hgvs_c'],'pvar':rvs['hgvs_p'],'transcript_id':rvs['enst']}
#VAR['consequence']=rvs['effect']
#print 'NO RVS, USING CSV INFO'
#ENSG00000164256:ENST00000296682:exon11:c.2497_2580del:p.833_860del
#variant=dict()
#variant['p_change'] = {'pvar': g['RVS']['impact']['hgvs_p'], 'cvar': g['RVS']['impact']['hgvs_c'], 'gene_id': gene_id, 'transcript_id': g['RVS']['impact']['enst']}
#variant['consequence'] = [g['RVS']['impact']['effect'], {'impact': g['RVS']['impact']['impact']} ]
#if g['RVS'].get('prediction',{}): temp = g['RVS']['prediction']
#for pred in ['Polyphen2_HDIV', 'SIFT', 'CADD', 'MutationTaster', 'ensemble_prediction', 'FATHMM', 'MutationAssessor', 'phastCons', 'GWAVA_region', 'Polyphen2_HVAR']: this['consequence'][1][pred] = temp[pred]
return rvs_vars
# query for annotated variants from vcf
vcfr = vcf.Reader( args.vcf )
for v in vcfr:
if len(v.FILTER)==0:
for alt in v.ALT:
chrom = v.CHROM.replace('chr','')
start = v.POS
alt = str(alt)
if v.is_snp or (not v.is_deletion and v.is_indel):
# snps or insertions
end = v.POS
elif v.is_deletion:
end = v.POS + (len(v.REF) - len(alt))
vkey = VarCharKey.v2k(chrom, start, end, alt)
for resource in resources:
# for n in rvs_collection.find({'chr' : str(chrom),
# 'start' : str(start),
# 'end' : str(end),
# 'alt' : alt,}):
# #'vkey' : vkey,
# # 'samples' : {'$in': vcfr.samples},
# #'resource' : resource}):
# pprint(n)
if rvs_collection.count({ 'vkey' : vkey,
'samples' : {'$in': vcfr.samples},
'resource' : resource}) == 0:
missing_vkeys[resource].add(vkey)
