def run(args):
start = timer()
Utilities.ensure_requisite_folders(args.output_prefix)
logging.info("Loading SNP annotation")
snp_key = KeyedDataSource.load_data(args.snp_annotation_file,
"varID",
"rsid_dbSNP150",
should_skip=KeyedDataSource.skip_na)
logging.info("Loading Genotype")
genotype, individual_ids = ModelTraining.load_genotype_folder(
args.input_genotype_folder, args.input_genotype_file_pattern, snp_key)
logging.info("Saving Genotype")
path_variant = args.output_prefix + ".variants.parquet"
Parquet.save_variants(path_variant, genotype, individual_ids)
path_metadata_variant = args.output_prefix + ".variants_metadata.parquet"
Parquet.save_metadata(path_metadata_variant, genotype)
logging.info("Processing Expression Phenotype")
expression_logic = Utilities.file_logic(
args.input_phenotype_folder, args.input_phenotype_expression_pattern)
for row in expression_logic.itertuples():
logging.info("Phenotype: %s", row.name)
process_phenotype(row.path, row.name, args.output_prefix)
end = timer()
logging.info("Finished in %s", str(end - start))
def generate_multi_backend(args, variant_key):
logging.info("Processing Genotype")
dosage_conversion = GenotypeUtilities.impute_to_mean_conversion if args.impute_to_mean else None
dosage_filter = get_filter(args, variant_key)
metadata = []
for genotype, individual_ids in ModelTraining.load_genotype_file_by_chromosome(
args.input_genotype_file, variant_key, dosage_conversion,
dosage_filter):
if args.simplify_individual_id:
logging.info("simplifying individual id")
individual_ids = [x.split("_")[0] for x in individual_ids]
_m = genotype.get_variants_metadata()
metadata.append(_m)
_chr = _m.chromosome.values[0]
logging.log(9, "Processing {}".format(_chr))
_o = args.output_prefix + ".chr{}".format(_chr) + ".variants.parquet"
Parquet.save_variants(_o, genotype, individual_ids)
logging.info("Saving metadata")
metadata = pandas.concat(metadata)
path_metadata_variant = args.output_prefix + ".variants_metadata.parquet"
Parquet._save_metadata(path_metadata_variant, metadata)
def generate_single_backend(args, variant_key):
logging.info("Loading Genotype")
dosage_conversion = GenotypeUtilities.impute_to_mean_conversion if args.impute_to_mean else None
dosage_filter = get_filter(args, variant_key)
genotype, individual_ids = ModelTraining.load_genotype_file(args.input_genotype_file, variant_key, dosage_conversion, dosage_filter)
logging.info("Saving Genotype")
path_variant = args.output_prefix + ".variants.parquet"
Parquet.save_variants(path_variant, genotype, individual_ids)
logging.info("Saving Genotype")
path_metadata_variant = args.output_prefix + ".variants_metadata.parquet"
Parquet.save_metadata(path_metadata_variant, genotype)