phenotype=tuple(i.folder._data for i in phen),
genotype=tuple(i.folder._data for i in gen),
covariates=tuple(i.folder._data.metadata for i in pard))
if row_index[2].shape[0] != np.sum(
[i.folder._data.metadata['id'].shape[0] for i in pard]):
raise ValueError(
'Partial Derivatives covariates have different number of subjects {} than genotype and phenotype {}'
.format(
row_index[2].shape[0],
np.sum([
i.folder._data.metadata['id'].shape[0]
for i in pard
])))
while True:
if mapper.cluster == 'n':
SNPs_index, keys = mapper.get()
else:
ch = mapper.chunk_pop()
if ch is None:
SNPs_index = None
break
SNPs_index, keys = mapper.get(chunk_number=ch)
if isinstance(SNPs_index, type(None)):
break
Analyser.rsid = keys
if np.sum(PD) == 0:
genotype = np.array([])
with Timer() as t_g:
genotype = merge_genotype(gen, SNPs_index, mapper)
meta_phen=MetaPhenotype(phen)
N_studies=len(args.genotype)
gen=[]
for i,j in enumerate(args.genotype):
gen.append(Reader('genotype'))
gen[i].start(j,hdf5=args.hdf5, study_name=args.study_name[i], ID=False)
#for i in gen:
# i._data.link()
row_index, ids = study_indexes(phenotype=tuple(i.folder._data for i in phen),genotype=tuple(i.folder._data for i in gen),covariates=tuple(i.folder._data.metadata for i in pard))
while True:
if mapper.cluster=='n':
SNPs_index, keys=mapper.get()
else:
ch=mapper.chunk_pop()
if ch is None:
SNPs_index=None
break
print ch
SNPs_index, keys=mapper.get(chunk_number=ch)
if isinstance(SNPs_index, type(None)):
break
Analyser.rsid=keys
if np.sum(PD)==0:
genotype=np.array([])
genotype=merge_genotype(gen, SNPs_index, mapper, flip_flag=False)
