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parse_genet.py
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parse_genet.py
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#!/usr/bin/env python
"""
Parse the reference panel, summary statistics, and validation set.
"""
import os
import numpy as np
from scipy.stats import norm
from scipy import linalg
import h5py
def parse_ref(ref_file, chrom):
print('... parse reference file: %s ...' % ref_file)
ref_dict = {'CHR':[], 'SNP':[], 'BP':[], 'A1':[], 'A2':[], 'MAF':[]}
with open(ref_file) as ff:
header = next(ff)
for line in ff:
ll = (line.strip()).split()
if int(ll[0]) == chrom:
ref_dict['CHR'].append(chrom)
ref_dict['SNP'].append(ll[1])
ref_dict['BP'].append(int(ll[2]))
ref_dict['A1'].append(ll[3])
ref_dict['A2'].append(ll[4])
ref_dict['MAF'].append(float(ll[5]))
print('... %d SNPs on chromosome %d read from %s ...' % (len(ref_dict['SNP']), chrom, ref_file))
return ref_dict
def parse_bim(bim_file, chrom):
print('... parse bim file: %s ...' % (bim_file + '.bim'))
vld_dict = {'SNP':[], 'A1':[], 'A2':[]}
with open(bim_file + '.bim') as ff:
for line in ff:
ll = (line.strip()).split()
if int(ll[0]) == chrom:
vld_dict['SNP'].append(ll[1])
vld_dict['A1'].append(ll[4])
vld_dict['A2'].append(ll[5])
print('... %d SNPs on chromosome %d read from %s ...' % (len(vld_dict['SNP']), chrom, bim_file + '.bim'))
return vld_dict
def parse_sumstats(ref_dict, vld_dict, sst_file, n_subj):
print('... parse sumstats file: %s ...' % sst_file)
ATGC = ['A', 'T', 'G', 'C']
sst_dict = {'SNP':[], 'A1':[], 'A2':[]}
with open(sst_file) as ff:
header = next(ff)
for line in ff:
ll = (line.strip()).split()
if ll[1] in ATGC and ll[2] in ATGC:
sst_dict['SNP'].append(ll[0])
sst_dict['A1'].append(ll[1])
sst_dict['A2'].append(ll[2])
print('... %d SNPs read from %s ...' % (len(sst_dict['SNP']), sst_file))
mapping = {'A': 'T', 'T': 'A', 'C': 'G', 'G': 'C'}
vld_snp = set(zip(vld_dict['SNP'], vld_dict['A1'], vld_dict['A2']))
ref_snp = set(zip(ref_dict['SNP'], ref_dict['A1'], ref_dict['A2'])) | set(zip(ref_dict['SNP'], ref_dict['A2'], ref_dict['A1'])) | \
set(zip(ref_dict['SNP'], [mapping[aa] for aa in ref_dict['A1']], [mapping[aa] for aa in ref_dict['A2']])) | \
set(zip(ref_dict['SNP'], [mapping[aa] for aa in ref_dict['A2']], [mapping[aa] for aa in ref_dict['A1']]))
sst_snp = set(zip(sst_dict['SNP'], sst_dict['A1'], sst_dict['A2'])) | set(zip(sst_dict['SNP'], sst_dict['A2'], sst_dict['A1'])) | \
set(zip(sst_dict['SNP'], [mapping[aa] for aa in sst_dict['A1']], [mapping[aa] for aa in sst_dict['A2']])) | \
set(zip(sst_dict['SNP'], [mapping[aa] for aa in sst_dict['A2']], [mapping[aa] for aa in sst_dict['A1']]))
comm_snp = vld_snp & ref_snp & sst_snp
print('... %d common SNPs in the reference, sumstats, and validation set ...' % len(comm_snp))
n_sqrt = np.sqrt(n_subj)
sst_eff = {}
with open(sst_file) as ff:
header = (next(ff).strip()).split()
header = [col.upper() for col in header]
for line in ff:
ll = (line.strip()).split()
snp = ll[0]; a1 = ll[1]; a2 = ll[2]
if a1 not in ATGC or a2 not in ATGC:
continue
if (snp, a1, a2) in comm_snp or (snp, mapping[a1], mapping[a2]) in comm_snp:
if 'BETA' in header:
beta = float(ll[3])
elif 'OR' in header:
beta = np.log(float(ll[3]))
if 'SE' in header:
se = float(ll[4])
beta_std = beta/se/n_sqrt
elif 'P' in header:
p = max(float(ll[4]), 1e-323)
beta_std = np.sign(beta)*abs(norm.ppf(p/2.0))/n_sqrt
sst_eff.update({snp: beta_std})
elif (snp, a2, a1) in comm_snp or (snp, mapping[a2], mapping[a1]) in comm_snp:
if 'BETA' in header:
beta = float(ll[3])
elif 'OR' in header:
beta = np.log(float(ll[3]))
if 'SE' in header:
se = float(ll[4])
beta_std = -1*beta/se/n_sqrt
elif 'P' in header:
p = max(float(ll[4]), 1e-323)
beta_std = -1*np.sign(beta)*abs(norm.ppf(p/2.0))/n_sqrt
sst_eff.update({snp: beta_std})
sst_dict = {'CHR':[], 'SNP':[], 'BP':[], 'A1':[], 'A2':[], 'MAF':[], 'BETA':[], 'FLP':[]}
for (ii, snp) in enumerate(ref_dict['SNP']):
if snp in sst_eff:
sst_dict['SNP'].append(snp)
sst_dict['CHR'].append(ref_dict['CHR'][ii])
sst_dict['BP'].append(ref_dict['BP'][ii])
sst_dict['BETA'].append(sst_eff[snp])
a1 = ref_dict['A1'][ii]; a2 = ref_dict['A2'][ii]
if (snp, a1, a2) in comm_snp:
sst_dict['A1'].append(a1)
sst_dict['A2'].append(a2)
sst_dict['MAF'].append(ref_dict['MAF'][ii])
sst_dict['FLP'].append(1)
elif (snp, a2, a1) in comm_snp:
sst_dict['A1'].append(a2)
sst_dict['A2'].append(a1)
sst_dict['MAF'].append(1-ref_dict['MAF'][ii])
sst_dict['FLP'].append(-1)
elif (snp, mapping[a1], mapping[a2]) in comm_snp:
sst_dict['A1'].append(mapping[a1])
sst_dict['A2'].append(mapping[a2])
sst_dict['MAF'].append(ref_dict['MAF'][ii])
sst_dict['FLP'].append(1)
elif (snp, mapping[a2], mapping[a1]) in comm_snp:
sst_dict['A1'].append(mapping[a2])
sst_dict['A2'].append(mapping[a1])
sst_dict['MAF'].append(1-ref_dict['MAF'][ii])
sst_dict['FLP'].append(-1)
return sst_dict
def parse_ldblk(ldblk_dir, sst_dict, chrom):
print('... parse reference LD on chromosome %d ...' % chrom)
if '1kg' in os.path.basename(ldblk_dir):
chr_name = ldblk_dir + '/ldblk_1kg_chr' + str(chrom) + '.hdf5'
elif 'ukbb' in os.path.basename(ldblk_dir):
chr_name = ldblk_dir + '/ldblk_ukbb_chr' + str(chrom) + '.hdf5'
hdf_chr = h5py.File(chr_name, 'r')
n_blk = len(hdf_chr)
ld_blk = [np.array(hdf_chr['blk_'+str(blk)]['ldblk']) for blk in range(1,n_blk+1)]
snp_blk = []
for blk in range(1,n_blk+1):
snp_blk.append([bb.decode("UTF-8") for bb in list(hdf_chr['blk_'+str(blk)]['snplist'])])
blk_size = []
mm = 0
for blk in range(n_blk):
idx = [ii for (ii, snp) in enumerate(snp_blk[blk]) if snp in sst_dict['SNP']]
blk_size.append(len(idx))
if idx != []:
idx_blk = range(mm,mm+len(idx))
flip = [sst_dict['FLP'][jj] for jj in idx_blk]
ld_blk[blk] = ld_blk[blk][np.ix_(idx,idx)]*np.outer(flip,flip)
_, s, v = linalg.svd(ld_blk[blk])
h = np.dot(v.T, np.dot(np.diag(s), v))
ld_blk[blk] = (ld_blk[blk]+h)/2
mm += len(idx)
else:
ld_blk[blk] = np.array([])
return ld_blk, blk_size