'If specified, the script will not terminate if some SNPs are not found in the meta file'
)
parser.add_argument(
'--q',
type=int,
default=100,
help=
'The maximum ratio between the largest and smallest prior causal probabilities'
)
args = parser.parse_args()
#check package versions
check_package_versions()
#configure logger
configure_logger(args.out)
#read sumtats file
logging.info('Loading sumstats files...')
t0 = time.time()
try:
df_snps = pd.read_parquet(args.sumstats)
except (ArrowIOError, ArrowInvalid):
df_snps = pd.read_table(args.sumstats, sep='\s+')
if 'A1' not in df_snps.columns:
raise ValueError('missing column A1')
if 'A2' not in df_snps.columns:
raise ValueError('missing column A2')
if 'CHR' not in df_snps.columns:
raise ValueError('missing column CHR')
if 'BP' not in df_snps.columns:
'If specified, S-LDSC will estimate non-negative taus using an exact instead of an approximate solver (this will be slower but slightly more accurate)'
)
#check package versions
check_package_versions()
#show splash screen
splash_screen()
#extract args
args = parser.parse_args()
#check that the output directory exists
if len(os.path.dirname(args.output_prefix)) > 0 and not os.path.exists(
os.path.dirname(args.output_prefix)):
raise ValueError('output directory %s doesn\'t exist' %
(os.path.dirname(args.output_prefix)))
#configure logger
configure_logger(args.output_prefix)
#check and fix args
args = check_args(args)
check_files(args)
#create and run PolyFun object
polyfun_obj = PolyFun()
polyfun_obj.polyfun_main(args)
print()
