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Intervar.py
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#!/usr/bin/env python
#########################################################################
# Author: Lee Quan ([email protected])
# Created Time: 2015-11-10 19:15:32 Tuesday
# File Name: InterVar.py File type: python
# Last Change:.
# Description: python script for Interpretation of Pathogenetic Benign
#########################################################################
import copy,logging,os,io,re,time,sys,platform,optparse,gzip
prog="InterVar"
version = """%prog 0.1
Written by Quan LI,[email protected].
InterVar is free for non-commercial use without warranty.
Please contact the authors for commercial use.
Copyright (C) 2016 Wang Genomic Lab
============================================================================
"""
usage = """Usage: %prog [OPTION] -i INPUT -o OUTPUT ...
%prog --config=config.ini ...
"""
description = """=============================================================================
InterVar
Interpretation of Pathogenic/Benign for variants using python scripts of InterVar.
=============================================================================
"""
end = """=============================================================================
Thanks for using InterVar!
Report bugs to [email protected];
InterVar homepage: <https://wInterVar.wglab.org>
=============================================================================
"""
if platform.python_version()< '3.0.0' :
import ConfigParser
else:
import configparser
paras = {}
def ConfigSectionMap(config,section):
global paras
options = config.options(section)
for option in options:
try:
paras[option] = config.get(section, option)
if paras[option] == -1:
DebugPrint("skip: %s" % option)
except:
print("exception on %s!" % option)
paras[option] = None
return
user_evidence_dict={}
class myGzipFile(gzip.GzipFile):
def __enter__(self):
if self.fileobj is None:
raise ValueError("I/O operation on closed GzipFile object")
return self
def __exit__(self, *args):
self.close()
#begin read some important datsets/list firstly;
lof_genes_dict={}
aa_changes_dict={}
domain_benign_dict={}
mim2gene_dict={}
mim2gene_dict2={}
morbidmap_dict={}
morbidmap_dict2={}
PP2_genes_dict={}
BP1_genes_dict={}
PS4_snps_dict={}
exclude_snps_dict={}
mim_recessive_dict={}
mim_domin_dict={}
mim_adultonset_dict={}
mim_pheno_dict={}
mim_orpha_dict={}
orpha_dict={}
BS2_snps_recess_dict={}
BS2_snps_domin_dict={}
knownGeneCanonical_dict={}
knownGeneCanonical_st_dict={}
knownGeneCanonical_ed_dict={}
def flip_ACGT(acgt):
nt="";
if acgt=="A":
nt="T"
if acgt=="T":
nt="A"
if acgt=="C":
nt="G"
if acgt=="G":
nt="C"
if acgt=="N":
nt="N"
if acgt=="X":
nt="X"
return(nt)
def read_datasets():
#0. read the user specified evidence file
if os.path.isfile(paras['evidence_file']):
try:
fh=open(paras['evidence_file'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
if len(cls2)>1:
keys=cls2[0]+"_"+cls2[1]+"_"+cls2[2]+"_"+cls2[3]
keys=re.sub("[Cc][Hh][Rr]","",keys)
#print("%s" %keys)
user_evidence_dict[keys]=cls2[4].upper()
except IOError:
print("Error: can\'t read the user specified evidence file %s" % paras['evidence_file'])
else:
fh.close()
#1.LOF gene list
try:
fh = open(paras['lof_genes'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
if len(cls2[0])>1:
lof_genes_dict[cls2[0]]='1'
except IOError:
print("Error: can\'t read the LOF genes file %s" % paras['lof_genes'])
print("Error: Please download it from the source website")
sys.exit()
return
else:
fh.close()
#2. AA change list
try:
fh = open(paras['ps1_aa'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
if len(cls2)>1 :
keys=cls2[0]+"_"+cls2[1]+"_"+cls2[2]+"_"+cls2[4]
keys=re.sub("[Cc][Hh][Rr]","",keys)
aa_changes_dict[keys]=cls2[6]
except IOError:
print("Error: can\'t read the amino acid change file %s" % paras['ps1_aa'])
print("Error: Please download it from the source website")
sys.exit()
else:
fh.close()
#3. Domain with benign
try:
fh = open(paras['pm1_domain'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
if len(cls2)>1:
keys=cls2[0]+"_"+cls2[1]+": "+cls2[2]
domain_benign_dict[keys]="1"
except IOError:
print("Error: can\'t read the PM1 domain file %s" % paras['pm1_domain'])
print("Error: Please download it from the source website")
sys.exit()
else:
fh.close()
#4. OMIM mim2gene.txt file
try:
fh = open(paras['mim2gene'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
if len(cls2)>1:
cls0=cls2[4].split(',')
keys=cls0[0]
mim2gene_dict[keys]=cls2[0]
keys1=cls2[3]
keys=keys1.upper()
mim2gene_dict2[keys]=cls2[0]
except IOError:
print("Error: can\'t read the OMIM file %s" % paras['mim2gene'])
print("Error: Please download it from http://www.omim.org/downloads")
sys.exit()
else:
fh.close()
#5.PP2 gene list
try:
fh = open(paras['pp2_genes'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
if len(cls2[0])>1:
PP2_genes_dict[cls2[0]]='1'
except IOError:
print("Error: can\'t read the PP2 genes file %s" % paras['PP2_genes'])
print("Error: Please download it from the source website")
sys.exit()
return
else:
fh.close()
#5.BP1 gene list
try:
fh = open(paras['bp1_genes'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
if len(cls2[0])>1:
BP1_genes_dict[cls2[0]]='1'
except IOError:
print("Error: can\'t read the BP1 genes file %s" % paras['BP1_genes'])
print("Error: Please download it from the source website")
sys.exit()
return
else:
fh.close()
#6.morbidmap from OMIM for BP5 , multifactorial disorders list
try:
fh = open(paras['morbidmap'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
#print("%s %s %d" % (cls2[0], cls[Funcanno_flgs['Gene']], len(cls2[0])) )
#{Tuberculosis, protection against}, 607948 (3)|TIRAP, BACTS1|606252|11q24.2
if len(cls2[0])>1 and cls2[0].find('{')==0: # disorder start with "{"
morbidmap_dict2[ cls2[2] ]='1' # key as mim number
for cls3 in cls2[1].split(', '):
keys=cls3.upper()
morbidmap_dict[ keys ]='1' # key as gene name
except IOError:
print("Error: can\'t read the OMIM morbidmap disorder file %s" % paras['morbidmap'])
print("Error: Please download it from http://www.omim.org/downloads")
sys.exit()
else:
fh.close()
#7.prevalence of the variant with OR>5 for PS4 , the dataset is from gwasdb jjwanglab.org/gwasdb
try:
fh = open(paras['ps4_snps'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
# PS4_snps_dict
if len(cls2[0])>=1: #
keys=cls2[0]+"_"+cls2[1]+"_"+cls2[1]+"_"+cls2[3]+"_"+cls2[4]
keys=re.sub("[Cc][Hh][Rr]","",keys)
PS4_snps_dict[ keys ]='1' # key as gene name
except IOError:
print("Error: can\'t read the snp list file for PS4 %s" % paras['ps4_snps'])
print("Error: Please download it from the source website")
sys.exit()
else:
fh.close()
#8. read the user specified SNP list, the variants will pass the frequency check.
if os.path.isfile(paras['exclude_snps']):
try:
fh=open(paras['exclude_snps'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
if len(cls2)>1:
keys=cls2[0]+"_"+cls2[1]+"_"+cls2[2]+"_"+cls2[3]
keys=re.sub("[Cc][Hh][Rr]","",keys)
exclude_snps_dict[keys]="1"
except IOError:
print("Error: can\'t read the user specified SNP list file %s" % paras['exclude_snps'])
else:
fh.close()
#9. OMIM mim_recessive.txt file mim_domin mim_adultonset
try:
fh = open(paras['mim_recessive'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
if len(cls2[0])>1:
mim_recessive_dict[cls2[0]]='1'
except IOError:
print("Error: can\'t read the OMIM recessive disorder file %s" % paras['mim_recessive'])
print("Error: Please download it from the source website")
sys.exit()
else:
fh.close()
try:
fh = open(paras['mim_domin'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
if len(cls2[0])>1:
mim_domin_dict[cls2[0]]='1'
except IOError:
print("Error: can\'t read the OMIM dominant disorder file %s" % paras['mim_domin'])
print("Error: Please download it from the source website")
sys.exit()
else:
fh.close()
try:
fh = open(paras['mim_adultonset'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
if len(cls2[0])>1:
mim_adultonset_dict[cls2[0]]='1'
except IOError:
print("Error: can\'t read the OMIM adult onset disorder file %s" % paras['mim_adultonset'])
print("Error: Please download it from the source website")
sys.exit()
else:
fh.close()
#10. knownGeneCanonical exon file # caution the build ver, now it is hg19
try:
fh = open(paras['knowngenecanonical'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split(' ')
if len(cls2)>1:
keys=cls2[0]
knownGeneCanonical_dict[keys]=cls2[1]
knownGeneCanonical_st_dict[keys]=cls2[2]
knownGeneCanonical_ed_dict[keys]=cls2[3]
#print("%s %s" %(keys,knownGeneCanonical_dict[keys]))
except IOError:
print("Error: can\'t read the knownGeneCanonical file %s" % paras['knowngenecanonical'])
print("Error: Please download it from the source website")
sys.exit()
else:
fh.close()
#11.BS2 variants of recessive homo, domin heter
try:
with myGzipFile(paras['bs2_snps'], "rb") as fh:
#fh = open(paras['bs2_snps'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split(' ')
# PS4_snps_dict
if len(cls2[0])>=1: #
keys=cls2[0]+"_"+cls2[1]+"_"+cls2[1]+"_"+cls2[2]+"_"+cls2[3]
#keys=re.sub("[Cc][Hh][Rr]","",keys)
BS2_snps_recess_dict[ keys ]=cls2[4] # key as snp info
BS2_snps_domin_dict[ keys ]=cls2[5] # key as snp info
keys=cls2[0]+"_"+cls2[1]+"_"+cls2[1]+"_"+flip_ACGT(cls2[2])+"_"+flip_ACGT(cls2[3])
#keys=re.sub("[Cc][Hh][Rr]","",keys)
BS2_snps_recess_dict[ keys ]=cls2[4] # key as snp info
BS2_snps_domin_dict[ keys ]=cls2[5] # key as snp info
except IOError:
print("Error: can\'t read the snp list file for BS2 %s" % paras['bs2_snps'])
print("Error: Please download it from the source website")
sys.exit()
else:
fh.close()
#12. OMIM mim_pheno.txt file
#mim_pheno = %(database_intervar)s/mim_pheno.txt
#mim_orpha = %(database_intervar)s/mim_orpha.txt
try:
fh = open(paras['mim_pheno'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split(' ')
if len(cls2)>1:
keys=cls2[0]
mim_pheno_dict[keys]=cls2[1]
#print("%s %s" %(keys,mim_pheno_dict[keys]))
except IOError:
print("Error: can\'t read the MIM file %s" % paras['mim_pheno'])
print("Error: Please download it from InterVar source website")
sys.exit()
else:
fh.close()
#13. OMIM mim_orpha.txt file
try:
fh = open(paras['mim_orpha'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split(' ')
if len(cls2)>1:
keys=cls2[0]
mim_orpha_dict[keys]=cls2[1]
#print("%s %s" %(keys,mim_orpha_dict[keys]))
except IOError:
print("Error: can\'t read the MIM file %s" % paras['mim_orpha'])
print("Error: Please download it from InterVar source website")
sys.exit()
else:
fh.close()
#14. orpha.txt file
try:
fh = open(paras['orpha'], "r")
str = fh.read()
for line2 in str.split('\n'):
cls2=line2.split('\t')
if len(cls2)>1:
keys=cls2[0]
orpha_dict[keys]=cls2[1]
#print("%s %s" %(keys,mim_orpha_dict[keys]))
except IOError:
print("Error: can\'t read the Orpha file %s" % paras['orpha'])
print("Error: Please download it from InterVar source website")
sys.exit()
else:
fh.close()
#end read datasets
return
def check_downdb():
path=paras['database_locat']
path=path.strip()
path=path.rstrip("\/")
isExists=os.path.exists(path)
if not isExists:
os.makedirs(path)
print("Notice: the folder of %s is created!" % path)
else:
print("Warning: the folder of %s is already created!" % path)
ds=paras['database_names']
ds.expandtabs(1);
# database_names = refGene 1000g2014oct esp6500siv2_all avsnp144 ljb26_all clinvar_20150629 exac03 hg19_dbscsnv11 dbnsfp31a_interpro rmsk ensGene
for dbs in ds.split():
# os.path.isfile(options.table_annovar)
file_name=dbs
if dbs=="1000g2014oct":
file_name="ALL.sites.2014_10"
if dbs=="1000g2015aug":
file_name="1000g2015aug"
dataset_file=paras['database_locat']+"/"+paras['buildver']+"_"+file_name+".txt"
if dbs != 'rmsk':
cmd="perl "+paras['annotate_variation']+" -buildver "+paras['buildver']+" -downdb -webfrom annovar "+file_name+" "+paras['database_locat']
if dbs == 'rmsk':
cmd="perl "+paras['annotate_variation']+" -buildver "+paras['buildver']+" -downdb "+file_name+" "+paras['database_locat']
if not os.path.isfile(dataset_file):
print("Warning: The Annovar dataset file of %s is not in %s,begin to download this %s ..." %(dbs,paras['database_locat'],dataset_file))
print("%s" %cmd)
os.system(cmd)
def check_input():
inputft= paras['inputfile_type']
if inputft.lower() == 'avinput' :
return
if inputft.lower() == 'vcf':
#convert2annovar.pl -format vcf4 variantfile > variant.avinput
cmd="perl "+paras['convert2annovar']+" -format vcf4 "+ paras['inputfile']+"> "+paras['inputfile']+".avinput"
print("Warning: Begin to convert your vcf file of %s to AVinput of Annovar ..." % paras['inputfile'])
print("%s" %cmd)
os.system(cmd)
return
def check_annovar_result():
# table_annovar.pl example/ex1.avinput humandb/ -buildver hg19 -out myanno -remove -protocol refGene,esp6500siv2_all,1000g2015aug_all,avsnp144,ljb26_all,CLINSIG,exac03 -operation g,f,f,f,f,f,f -nastring . -csvout
inputft= paras['inputfile_type']
if inputft.lower() == 'avinput' :
cmd="perl "+paras['table_annovar']+" "+paras['inputfile']+" "+paras['database_locat']+" -buildver "+paras['buildver']+" -remove -out "+ paras['outfile']+" -protocol refGene,esp6500siv2_all,1000g2015aug_all,avsnp144,dbnsfp30a,clinvar_20160302,exac03,dbscsnv11,dbnsfp31a_interpro,rmsk,ensGene,knownGene -operation g,f,f,f,f,f,f,f,f,r,g,g -nastring ."
else:
cmd="perl "+paras['table_annovar']+" "+paras['inputfile']+".avinput "+paras['database_locat']+" -buildver "+paras['buildver']+" -remove -out "+ paras['outfile']+" -protocol refGene,esp6500siv2_all,1000g2015aug_all,avsnp144,dbnsfp30a,clinvar_20160302,exac03,dbscsnv11,dbnsfp31a_interpro,rmsk,ensGene,knownGene -operation g,f,f,f,f,f,f,f,f,r,g,g -nastring ."
print("%s" %cmd)
os.system(cmd)
return
def get_gdi_rvis_lof(gene_name,line_out,dicts,temple):
try:
line_out=line_out+"\t"+'\t'.join(str(e) for e in dicts[gene_name])
except KeyError:
line_out=line_out+"\t"+'\t'.join(str(e) for e in temple)
else:
pass
return(line_out)
def check_gdi_rvis_LOF(anvfile):
gdi={}
rvis={}
lof={}
newoutfile=anvfile+".grl_p"
# begin open file and set dicts for gdi rvis and lof:
try:
fh = open(paras['gdi_file'], "r")
str = fh.read()
for line in str.split('\n'):
cls=line.split('\t')
if len(cls)>1:
gdi[cls[0]]=cls[1:]
except IOError:
print("Error: can\'t read the annovar output file %s" % paras['gdi_file'])
sys.exit()
return
else:
pass
fh.close()
try:
fh = open(paras['rvis_file'], "r")
str = fh.read()
for line in str.split('\n'):
cls=line.split('\t')
rvis['Gene']=['RVIS_ExAC_0.05%(AnyPopn)','%RVIS_ExAC_0.05%(AnyPopn)']
if len(cls)>1:
rvis[cls[4]]=cls[5:]
except IOError:
print("Error: can\'t read the annovar output file %s" % paras['rvis_file'])
sys.exit()
return
else:
pass
fh.close()
try:
fh = open(paras['lof_file'], "r")
str = fh.read()
for line in str.split('\n'):
cls=line.split('\t')
if len(cls)>1:
lof[cls[0]]=cls[1:]
except IOError:
print("Error: can\'t read the annovar output file %s" % paras['lof_file'])
sys.exit()
return
else:
pass
fh.close()
try:
fh = open(anvfile, "r")
fw = open(newoutfile, "w")
str = fh.read()
sum=0
for line in str.split('\n'):
cls=line.split('\t')
if len(cls)>1:
gene_name=cls[6]
if cls[6] == 'Gene.refGene':
gene_name='Gene'
#some with multiple genes, so one gene by one gene to annote
gdi_temp=['.', '.', '.', '.', '.', '.', '.', '.', '.', '.', '.', '.']
rvis_temp=['.', '.']
lof_temp=['.']
sum=sum+1
for gg in gene_name.split(','):
line_out=line+"\t"+gg
line_out=get_gdi_rvis_lof(gg,line_out,gdi,gdi_temp)
line_out=get_gdi_rvis_lof(gg,line_out,rvis,rvis_temp)
line_out=get_gdi_rvis_lof(gg,line_out,lof,lof_temp)
fw.write("%s\n" % line_out)
# fh.write("This is my test file for exception handling!!")
except IOError:
print("Error: can\'t read/write the annovar output file %s %s" % (anvfile,newoutfile))
sys.exit()
return
else:
pass
fh.close()
fw.close()
return(sum)
def check_genes(anvfile):
#check with multiple genes, so one gene by one gene to annote
newoutfile=anvfile+".grl_p"
try:
fh = open(anvfile, "r")
fw = open(newoutfile, "w")
str = fh.read()
sum=0
for line in str.split('\n'):
cls=line.split('\t')
if len(cls)>1:
gene_name=cls[6]
if cls[6] == 'Gene.refGene':
gene_name='Gene'
#some with multiple genes, so one gene by one gene to annote
sum=sum+1
for gg in gene_name.split(','):
line_out=re.sub("^[Cc][Hh][Rr]","",line)+"\t"+gg
#line_out=line+"\t"+gg
# re.sub("[Cc][Hh][Rr]","",keys)
fw.write("%s\t\n" % line_out)
except IOError:
print("Error: can\'t read/write the annovar output file %s %s" % (anvfile,newoutfile))
sys.exit()
return
else:
pass
fh.close()
fw.close()
return(sum)
def sum_of_list(list):
sum=0
for i in list:
sum=sum+i
return(sum)
def classfy(PVS1,PS,PM,PP,BA1,BS,BP,Allels_flgs,cls):
BPS=["Pathogenic","Likely pathogenic","Benign","Likely benign","Uncertain significance"]
PAS_out=-1
BES_out=-1
BPS_out=4 # BPS=[4]:Uncertain significance
PS_sum=sum_of_list(PS)
PM_sum=sum_of_list(PM)
PP_sum=sum_of_list(PP)
BS_sum=sum_of_list(BS)
BP_sum=sum_of_list(BP)
#print("Before up/down grade, the sum of PS %s, PM %s,PP %s,BS %s,BP %s" %(PS_sum,PM_sum,PP_sum,BS_sum,BP_sum));
#begin process the user's flexible grade to get the final interpretation
if os.path.isfile(paras['evidence_file']):
keys=cls[Allels_flgs['Chr']]+"_"+cls[Allels_flgs['Start']]+"_"+cls[Allels_flgs['Ref']]+"_"+cls[Allels_flgs['Alt']]
keys=re.sub("[Cc][Hh][Rr]","",keys)
try:
evds=user_evidence_dict[keys] #PS1=1;PM1=1;BA1=1;PVS1 PP BS BP
for evd in evds.split(';'):
evd_t=evd.split('=')
if(len(evd_t)>1 and re.findall('grade', evd_t[0], flags=re.IGNORECASE) ):
#10 104353782 G A PVS1=1;PP1=1;PM3=1;grade_PP1=2;
if int(evd_t[1])<=3:
#print ("%s %s %s " %(keys,evd_t[1],evd_t[0]))
if(evd_t[0].find('PS')!=-1):
t=evd_t[0].find('PS');
tt=evd_t[0];
tt3=int(tt[t+2:t+3])
PS_sum=PS_sum-1
if(t<len(evd_t[0])-2 and tt3<=5 ):
if int(evd_t[1]) ==1 :
PS_sum=PS_sum+1
if int(evd_t[1]) ==2 :
PM_sum=PM_sum+1
if int(evd_t[1]) ==3 :
PP_sum=PP_sum+1
if(evd_t[0].find('PM')!=-1):
t=evd_t[0].find('PM');
tt=evd_t[0];
tt3=int(tt[t+2:t+3])
PM_sum=PM_sum-1
if(t<len(evd_t[0])-2 and tt3<=7 ):
if int(evd_t[1]) ==1 :
PS_sum=PS_sum+1
if int(evd_t[1]) ==2 :
PM_sum=PM_sum+1
if int(evd_t[1]) ==3 :
PP_sum=PP_sum+1
if(evd_t[0].find('PP')!=-1):
t=evd_t[0].find('PP');
tt=evd_t[0];
tt3=int(tt[t+2:t+3])
PP_sum=PP_sum-1
if(t<len(evd_t[0])-2 and tt3<=6 ):
if int(evd_t[1]) ==1 :
PS_sum=PS_sum+1
if int(evd_t[1]) ==2 :
PM_sum=PM_sum+1
if int(evd_t[1]) ==3 :
PP_sum=PP_sum+1
if(evd_t[0].find('BS')!=-1):
t=evd_t[0].find('BS');
tt=evd_t[0];
tt3=int(tt[t+2:t+3])
BS_sum=BS_sum-1
if(t<len(evd_t[0])-2 and tt3<=5 ):
if int(evd_t[1]) ==1 :
BS_sum=BS_sum+1
if int(evd_t[1]) ==3 :
BP_sum=BP_sum+1
if(evd_t[0].find('BP')!=-1):
t=evd_t[0].find('BP');
tt=evd_t[0];
tt3=int(tt[t+2:t+3])
BP_sum=BP_sum-1
if(t<len(evd_t[0])-2 and tt3<=8 ):
if int(evd_t[1]) ==1 :
BS_sum=BS_sum+1
if int(evd_t[1]) ==3 :
BP_sum=BP_sum+1
except KeyError:
pass
else:
pass
# end process the user's flexible grade
#print("After up/down grade, the sum of PS %s, PM %s,PP %s,BS %s,BP %s" %(PS_sum,PM_sum,PP_sum,BS_sum,BP_sum));
#print("%d %d %d %d %d " %(PS_sum,PM_sum,PP_sum,BS_sum, BP_sum))
if PS_sum ==1:
if PM_sum ==1 or PM_sum ==2: PAS_out=1
if PVS1 ==1 :
if PM_sum ==1: PAS_out=1 # 1:Likely pathogenic
if PS_sum ==1 and PP_sum >=2: PAS_out=1
if PM_sum >=3: PAS_out=1
if PM_sum ==2 and PP_sum >=2: PAS_out=1
if PM_sum ==1 and PP_sum >=4: PAS_out=1
if PVS1 ==1 :
if PS_sum >=1: PAS_out=0 # 0:Pathogenic
if PM_sum >=2: PAS_out=0
if PM_sum ==1 and PP_sum ==1: PAS_out=0
if PP_sum >=2: PAS_out=0
if PS_sum >=2: PAS_out=0
if PS_sum ==1:
if PM_sum >=3: PAS_out=0
if PM_sum ==2 and PP_sum >=2: PAS_out=0
if PM_sum ==1 and PP_sum >=4: PAS_out=0
if BS_sum==1 and BP_sum==1 :BES_out=3 #3:Likely benign
if BP_sum>=2 :BES_out=3
if BA1 ==1 or BS_sum>=2 : BES_out=2 #2:Benign
if PAS_out != -1 and BES_out == -1: BPS_out=PAS_out
if PAS_out == -1 and BES_out != -1: BPS_out=BES_out
if PAS_out == -1 and BES_out == -1: BPS_out=4
if PAS_out != -1 and BES_out != -1: BPS_out=4
#print("%d %d %d " %(PAS_out,BES_out,BPS_out))
return(BPS[BPS_out])
def check_PVS1(line,Funcanno_flgs,Allels_flgs,lof_genes_dict):
'''
Certain types of variants (e.g., nonsense, frameshift, canonical
+- 1 or 2 splice sites, initiation codon, single exon or multiexon
deletion) in a gene where LOF is a known mechanism of disease
'''
cls=line.split('\t')
funcs_tmp=["nonsense","frameshift","splic","stopgain"]
funcs_tmp2="nonframe"
line_tmp=cls[Funcanno_flgs['Func.refGene']]+" "+cls[Funcanno_flgs['ExonicFunc.refGene']]
PVS=0
PVS_t1=0
PVS_t2=0
PVS_t3=0
dbscSNV_cutoff=0.6 #either score(ada and rf) >0.6 as splicealtering
# Funcanno_flgs={'Func.refGene':0,'ExonicFunc.refGene':0
for fc in funcs_tmp:
if line_tmp.find(fc)>=0 and line_tmp.find(funcs_tmp2)<0 :
PVS_t1=1
break
# wait to check LOF genes use the LoFtool_percentile,but how to know is the disese mechanism
try:
if lof_genes_dict[ cls[Funcanno_flgs['Gene']] ] == '1' :
PVS_t2=1
except KeyError:
PVS_t2=0
else:
pass
#print("PVSt1= %d PVSt2= %d" % (PVS_t1,PVS_t2) )
# begin check the site in not affect the splicing
try:
if float(cls[Funcanno_flgs['dbscSNV_RF_SCORE']])>dbscSNV_cutoff or float(cls[Funcanno_flgs['dbscSNV_ADA_SCORE']])>dbscSNV_cutoff:
PVS_t3=1
except ValueError:
pass
else:
pass
if PVS_t1 !=0 and PVS_t2 != 0 :
if PVS_t3 ==0:
PVS=1
#begin check it in the AAChange.knownGene for the major/Canonical isoform, not 1/last exon
#SUFU:uc001kvy.2:exon6:c.G716A:p.R239Q
line_tmp2=cls[Funcanno_flgs['AAChange.knownGene']]
cls0=line_tmp2.split(',')
cls0_1=cls0[0].split(':')
if len(cls0_1)>1:
trans_id=cls0_1[1]
exon=cls0_1[2]
try:
exon_lth="exon"+knownGeneCanonical_dict[trans_id]
if exon==exon_lth or exon =="exon1": # not 1 or last exon
PVS=0
try:
if (float(knownGeneCanonical_ed_dict[trans_id])-float( cls[Allels_flgs['Start']] ))<50: # means close 3' of gene 50 bp.
PVS=0
except ValueError:
pass
else:
pass
except KeyError:
pass
else:
pass
return(PVS)
def check_PS1(line,Funcanno_flgs,Allels_flgs,aa_changes_dict):
'''
PS1 Same amino acid change as a previously established pathogenic variant regardless of nucleotide change
Example: Val->Leu caused by either G>C or G>T in the same codon
AAChange.refGene
NOD2:NM_001293557:exon3:c.C2023T:p.R675W,NOD2:NM_022162:exon4:c.C2104T:p.R702W
'''
PS1=0
PS1_t1=0
PS1_t2=0
PS1_t3=0
dbscSNV_cutoff=0.6 #either score(ada and rf) >0.6 as splicealtering
cls=line.split('\t')
funcs_tmp=["missense","nonsynony"]
ACGTs=["A","C","G","T"]
line_tmp=cls[Funcanno_flgs['Func.refGene']]+" "+cls[Funcanno_flgs['ExonicFunc.refGene']]
for fc in funcs_tmp:
if line_tmp.find(fc)>=0 :
PS1_t1=1;
# need to wait to check Same amino acid change as a previously pathogenic variant
line_tmp2=cls[Funcanno_flgs['AAChange.refGene']]
cls0=line_tmp2.split(',')
cls0_1=cls0[0].split(':')
aa=cls0_1[4]
aa_last=aa[len(aa)-1:]
keys_tmp2=cls[Allels_flgs['Chr']]+"_"+cls[Allels_flgs['Start']]+"_"+cls[Allels_flgs['End']]+"_"+cls[Allels_flgs['Alt']]
try:
if aa_changes_dict[keys_tmp2]:
PS1_t2=0
except KeyError:
for nt in ACGTs:
if nt != cls[Allels_flgs['Alt']]:
keys_tmp3=cls[Allels_flgs['Chr']]+"_"+cls[Allels_flgs['Start']]+"_"+cls[Allels_flgs['End']]+"_"+nt
try:
if aa_changes_dict[keys_tmp3] == aa_last:
PS1_t2=1
except KeyError:
pass
else:
pass
else:
pass
try:
if float(cls[Funcanno_flgs['dbscSNV_RF_SCORE']])>dbscSNV_cutoff or float(cls[Funcanno_flgs['dbscSNV_ADA_SCORE']])>dbscSNV_cutoff: # means alter the splicing
PS1_t3=1
except ValueError:
pass
else:
pass
if PS1_t1 !=0 and PS1_t2 != 0 :
if PS1_t3 ==1: # remove the splicing affect
PS1=0
return(PS1)
def check_PS2(line,Funcanno_flgs,Allels_flgs):
'''
De novo (both maternity and paternity confirmed) in a patient with the disease and no family history
'''
PS2=0
return(PS2)
def check_PS3(line,Funcanno_flgs,Allels_flgs):
'''
Well-established in vitro or in vivo functional studies supportive of a damaging effect on the gene or gene
product
'''
PS3=0
'''
cls=line.split('\t')
line_tmp=cls[Funcanno_flgs['Gene damage prediction (all disease-causing genes)']]
funcs_tmp=["missense","nonsynony"]
line_tmp2=cls[Funcanno_flgs['Func.refGene']]+" "+cls[Funcanno_flgs['ExonicFunc.refGene']]
for fc in funcs_tmp:
#if line_tmp == 'Medium' or line_tmp == 'High':
if line_tmp2.find(fc)>=0 and (line_tmp == 'High') :
PS3=1
'''
return(PS3)
def check_PS4(line,Funcanno_flgs,Allels_flgs):
'''
The prevalence of the variant in affected individuals is significantly increased compared with the prevalence
in controls; OR>5 in all the gwas, the dataset is from gwasdb jjwanglab.org/gwasdb
'''
PS4=0
cls=line.split('\t')
keys_tmp2=cls[Allels_flgs['Chr']]+"_"+cls[Allels_flgs['Start']]+"_"+cls[Allels_flgs['End']]+"_"+cls[Allels_flgs['Ref']]+"_"+cls[Allels_flgs['Alt']]
try:
if PS4_snps_dict[keys_tmp2] == "1":
PS4=1
except KeyError:
pass
else:
pass
return(PS4)
def check_PM1(line,Funcanno_flgs,Allels_flgs,domain_benign_dict):
'''
Located in a mutational hot spot and/or critical and well-established functional domain (e.g., active site of
an enzyme) without benign variation
'''
PM1=0
PM1_t1=0
PM1_t2=0
cls=line.split('\t')
funcs_tmp=["missense","nonsynony"]
line_tmp=cls[Funcanno_flgs['Func.refGene']]+" "+cls[Funcanno_flgs['ExonicFunc.refGene']]
for fc in funcs_tmp:
if line_tmp.find(fc)>=0 :
PM1_t1=1;
# need to wait to check whether in hot spot or functional domain/without benign variation
if cls[Funcanno_flgs['Interpro_domain']]!= '.' :
keys_tmp2=cls[Allels_flgs['Chr']]+"_"+cls[Funcanno_flgs['Gene']]+": "+cls[Funcanno_flgs['Interpro_domain']]
try:
if domain_benign_dict[keys_tmp2] =="1":
PM1_t2=0
except KeyError:
PM1_t2=1
else:
pass
if PM1_t1==1 and PM1_t2==1 :
PM1=1
return(PM1)
def check_PM2(line,Freqs_flgs,Allels_flgs,Funcanno_flgs,mim2gene_dict,mim2gene_dict2):
'''
Absent from controls (or at extremely low frequency if recessive) (Table 6) in Exome Sequencing Project,
1000 Genomes Project, or Exome Aggregation Consortium
'''
PM2=0
cutoff_maf=0.001 # extremely low frequency
cls=line.split('\t')
tt=1;
for key in Freqs_flgs.keys():
if(cls[Freqs_flgs[key]]!='.'): # absent in all three controls
tt=tt*0;
if tt==1:
PM2=1
if tt==0: # means some controls has frequency and it is not absent; then need to check it is recessive or not
tt2=1;
try:
mim2=mim2gene_dict2[cls[Funcanno_flgs['Gene']]]
mim1=mim2gene_dict[ cls[Funcanno_flgs['Gene.ensGene']] ]
try:
if mim_recessive_dict[mim2]=="1" or mim_recessive_dict[mim1]=="1": # it is recessive
for key in Freqs_flgs.keys():
if(cls[Freqs_flgs[key]]!='.' and float(cls[Freqs_flgs[key]])>=cutoff_maf):
tt2=tt2*0;
if tt2==1:
PM2=1
if tt2==0:
PM2=0
except KeyError: # means it is not recessive
PM2=0
else:
pass
except KeyError: # it has no mim, also treat as dom and not absent
PM2=0
else:
pass