random_effect_intercept=args.effect_intercept)
else:
a_test, b_cov, C, a_cov, b4 = meta_pard.get(
SNPs_index=SNPs_index,
B4=True,
regression_model=regression_model,
random_effect_intercept=args.effect_intercept)
print "Time to get PD {}s".format(t_pd.secs)
MAF = meta_pard.maf_pard(SNPs_index=SNPs_index)
if args.maf != 0:
filter = (MAF > args.maf) & (MAF < 1 - args.maf) & (MAF != 0.5)
a_test = a_test[filter, :]
Analyser.MAF = MAF[filter]
if np.sum(PD) == 0:
genotype = genotype[filter, :]
else:
b4 = b4[filter, :]
Analyser.rsid = Analyser.rsid[filter]
if a_test.shape[0] == 0:
print 'NO SNPs > MAF'
continue
else:
Analyser.MAF = MAF
a_inv = A_inverse(a_cov, a_test)
N_con = a_inv.shape[1] - 1
print 'There are {} subjects in study.'.format(
meta_pard.get_n_id())
if protocol.enable:
regression_model=protocol.regression_model()
else:
regression_model=None
if np.sum(PD)==0:
a_test, b_cov, C, a_cov = meta_pard.get( SNPs_index=SNPs_index, regression_model=regression_model, random_effect_intercept=args.effect_intercept)
else:
a_test, b_cov, C, a_cov, b4 = meta_pard.get( SNPs_index=SNPs_index, B4=True, regression_model=regression_model, random_effect_intercept=args.effect_intercept)
MAF=meta_pard.maf_pard(SNPs_index=SNPs_index)
if args.maf!=0:
filter=(MAF>args.maf) & (MAF<1-args.maf) & (MAF!=0.5)
a_test=a_test[filter,:]
Analyser.MAF=MAF[filter]
if np.sum(PD)==0:
genotype=genotype[filter,:]
else:
b4=b4[filter,:]
Analyser.rsid=Analyser.rsid[filter]
if a_test.shape[0]==0:
print 'NO SNPs > MAF'
continue
else:
Analyser.MAF=MAF
a_inv=A_inverse(a_cov, a_test)
N_con=a_inv.shape[1] - 1
print 'There are {} subjects in study.'.format(meta_pard.get_n_id())
DF=( meta_pard.get_n_id()- a_inv.shape[1] )
