def _read_chr_split_files(chr_arg, not_chr_arg, log, noun, parsefunc, **kwargs):
'''Read files split across 22 chromosomes (annot, ref_ld, w_ld).'''
try:
if not_chr_arg:
log.log('Reading {N} from {F} ...'.format(F=not_chr_arg, N=noun))
out = parsefunc(_splitp(not_chr_arg), **kwargs)
elif chr_arg:
f = ps.sub_chr(chr_arg, '[1-22]')
log.log('Reading {N} from {F} ...'.format(F=f, N=noun))
out = parsefunc(_splitp(chr_arg), _N_CHR, **kwargs)
except ValueError as e:
log.log('Error parsing {N}.'.format(N=noun))
raise e
return out
def _read_chr_split_files(chr_arg, not_chr_arg, log, noun, parsefunc, **kwargs):
'''Read files split across 22 chromosomes (annot, ref_ld, w_ld).'''
try:
if not_chr_arg:
log.log('Reading {N} from {F} ...'.format(F=not_chr_arg, N=noun))
out = parsefunc(_splitp(not_chr_arg), **kwargs)
elif chr_arg:
f = ps.sub_chr(chr_arg, '[1-22]')
log.log('Reading {N} from {F} ...'.format(F=f, N=noun))
out = parsefunc(_splitp(chr_arg), _N_CHR, **kwargs)
except ValueError as e:
log.log('Error parsing {N}.'.format(N=noun))
raise e
return out
def _read_header(args):
'''Read header from .expscore files'''
if args.exp_chr:
f = ps.sub_chr(args.exp_chr, 1) + '.expscore'
comp = ps.which_compression(f)
indices, cnames, cgroups = ps.filter_columns(f + comp[0],
comp[1],
fsuffix='expscore',
args=args)
cnames = [x for x in cnames if x not in ['SNP', 'CHR', 'BP', 'CM']]
else:
f = args.exp + '.expscore'
comp = ps.which_compression(f)
indices, cnames, cgroups = ps.filter_columns(f + comp[0],
comp[1],
fsuffix='expscore',
args=args)
cnames = [x for x in cnames if x not in ['SNP', 'CHR', 'BP', 'CM']]
return indices, cnames, cgroups
def _read_multiple_chr_split_files(chr_arg_array, not_chr_arg_array, log, noun,
parsefunc, **kwargs):
'''Read files split across 22 chromosomes (annot, ref_ld, w_ld).'''
try:
if not_chr_arg_array:
fh_list = []
for not_chr_arg in not_chr_arg_array:
log.log('Reading {N} from {F} ...'.format(F=not_chr_arg,
N=noun))
fh_list += _splitp(not_chr_arg)
out = parsefunc(fh_lit, **kwargs)
elif chr_arg_array:
fh_list = []
for chr_arg in chr_arg_array:
f = ps.sub_chr(chr_arg, '[1-22]')
log.log('Reading {N} from {F} ...'.format(F=f, N=noun))
fh_list += _splitp(chr_arg)
out = parsefunc(fh_list, _N_CHR, **kwargs)
except ValueError as e:
log.log('Error parsing {N}.'.format(N=noun))
raise e
return out
def _read_nonneg_constraints(args, log, snp_names, ref_ld_cnames):
assert args.ref_ld_chr or args.ref_ld is not None, 'non-negative constraints must be used with --ref_ld_chr or --ref_ld'
noun = 'annot matrix'
try:
#read annotation files
if args.ref_ld_chr is not None:
f = ps.sub_chr(args.ref_ld_chr, '[1-22]')
log.log('Reading {N} from {F} ...'.format(F=f, N=noun))
fh_list = _splitp(args.ref_ld_chr)
else:
f = args.ref_ld
log.log('Reading {N} from {F} ...'.format(F=f, N=noun))
fh_list = _splitp(args.ref_ld)
df_annotations_list = []
columns_list = []
for fh in fh_list:
df_annotations_list_fh = []
if args.ref_ld_chr is not None:
flist_small = [ps.sub_chr(fh, chr) + '.annot_small.gz' for chr in xrange(1, _N_CHR + 1)]
flist_notsmall = [ps.sub_chr(fh, chr) + '.annot.gz' for chr in xrange(1, _N_CHR + 1)]
else:
flist_small = [fh + '.annot_small.gz']
flist_notsmall = [fh + '.annot.gz']
for f_i in xrange(len(flist_small)):
fname = flist_small[f_i]
if (not os.path.exists(fname)):
fname = flist_notsmall[f_i]
df_annotations_chr = pd.read_csv(fname, delim_whitespace=True)
# if not args.constrain_all_snps:
# df_annotations_chr = df_annotations_chr.loc[df_annotations_chr['SNP'].isin(snp_names)]
df_annotations_chr.set_index(df_annotations_chr.columns[:4].tolist(), drop=True, inplace=True)
if (args.anno is not None):
annotations = args.anno.split(',')
#for a in annotations:
# assert a in df_annotations_chr.columns
df_annotations_chr = df_annotations_chr.loc[:, [c for c in df_annotations_chr.columns if (c in annotations)]]
df_annotations_list_fh.append(df_annotations_chr)
df_fh = pd.concat(df_annotations_list_fh, axis=0)
columns_list += df_fh.columns.tolist()
df_annotations_list.append(df_fh)
assert len(np.unique(columns_list)) == len(columns_list), 'duplicate columns exist in different annotation files'
df_annotations = reduce(lambda left,right: pd.merge(left,right,left_index=True, right_index=True), df_annotations_list)
del df_annotations_list
df_annotations.drop_duplicates(inplace=True)
log.log('%d constraints remained after removing duplicate constraints'%(df_annotations.shape[0]))
# if not args.constrain_all_snps:
# assert (df_annotations.index.get_level_values(2) == snp_names).all() #SNP Names
#define tau constraints
annotation_names = [(c[:c.index('L2')] if ('L2' in c) else c) for c in ref_ld_cnames]
assert (df_annotations.columns == annotation_names).all()
#add intercept column if required
if (args.intercept_h2 is None and not args.no_intercept):
df_annotations['intercept'] = np.zeros(df_annotations.shape[0])
return df_annotations.astype(np.float)
except ValueError as e:
log.log('Error parsing {N}.'.format(N=noun))
raise e
