def test_genetics_evidence_string(self):
"""Verifies expected genetics evidence string generation."""
evidence_string = json.dumps(
evidence_strings.CTTVGeneticsEvidenceString(*self.test_args),
sort_keys=True,
indent=2)
expected_evidence_string = open(
config.expected_genetics_evidence_string).read()
self.assertEqual(evidence_string, expected_evidence_string)
def clinvar_to_evidence_strings(allowed_clinical_significance, mappings,
json_file, ot_schema):
report = Report(trait_mappings=mappings.trait_2_efo)
cell_recs = cellbase_records.CellbaseRecords(json_file=json_file)
ot_schema_contents = json.loads(open(ot_schema).read())
for cellbase_record in cell_recs:
report.counters["record_counter"] += 1
if report.counters["record_counter"] % 1000 == 0:
logger.info("{} records processed".format(
report.counters["record_counter"]))
n_ev_strings_per_record = 0
clinvar_record = clinvar.ClinvarRecord(cellbase_record['clinvarSet'])
for clinvar_record_measure in clinvar_record.measures:
report.counters["n_nsvs"] += (clinvar_record_measure.nsv_id
is not None)
append_nsv(report.nsv_list, clinvar_record_measure)
report.counters["n_multiple_allele_origin"] += (len(
clinvar_record.allele_origins) > 1)
traits = create_traits(clinvar_record.traits, mappings.trait_2_efo,
report)
converted_allele_origins = convert_allele_origins(
clinvar_record.allele_origins)
for consequence_type, trait, allele_origin in itertools.product(
get_consequence_types(clinvar_record_measure,
mappings.consequence_type_dict),
traits, converted_allele_origins):
if skip_record(clinvar_record, clinvar_record_measure,
consequence_type, allele_origin,
allowed_clinical_significance, report):
continue
if allele_origin == 'germline':
evidence_string = evidence_strings.CTTVGeneticsEvidenceString(
clinvar_record, clinvar_record_measure, report, trait,
consequence_type)
elif allele_origin == 'somatic':
evidence_string = evidence_strings.CTTVSomaticEvidenceString(
clinvar_record, clinvar_record_measure, report, trait,
consequence_type)
report.add_evidence_string(evidence_string, clinvar_record,
trait,
consequence_type.ensembl_gene_id,
ot_schema_contents)
report.evidence_list.append([
clinvar_record.accession, clinvar_record_measure.rs_id,
trait.clinvar_name, trait.ontology_id
])
report.counters["n_valid_rs_and_nsv"] += (
clinvar_record_measure.nsv_id is not None)
report.traits.add(trait.ontology_id)
report.remove_trait_mapping(trait.clinvar_name)
report.ensembl_gene_id_uris.add(
evidence_strings.get_ensembl_gene_id_uri(
consequence_type.ensembl_gene_id))
n_ev_strings_per_record += 1
if n_ev_strings_per_record > 0:
report.counters["n_processed_clinvar_records"] += 1
if n_ev_strings_per_record > 1:
report.counters["n_multiple_evidence_strings"] += 1
return report
def setUp(self):
self.test_args = get_input_data_for_evidence_string_generation()
self.test_ges = evidence_strings.CTTVGeneticsEvidenceString(
*self.test_args)
self.ot_schema_contents = json.loads(
gzip.open(config.open_targets_schema_gz).read().decode('utf-8'))
def test_validate(self):
test_args = get_input_data_for_evidence_string_generation()
test_evidence_string = evidence_strings.CTTVGeneticsEvidenceString(
*test_args)
self.assertTrue(test_evidence_string.validate(self.ot_schema_contents))
def clinvar_to_evidence_strings(allowed_clinical_significance, mappings,
json_file, ot_schema, output_evidence_strings):
report = Report(trait_mappings=mappings.trait_2_efo)
cell_recs = cellbase_records.CellbaseRecords(json_file=json_file)
ot_schema_contents = json.loads(open(ot_schema).read())
output_evidence_strings_file = utilities.open_file(output_evidence_strings,
'wt')
for cellbase_record in cell_recs:
report.counters["record_counter"] += 1
if report.counters["record_counter"] % 1000 == 0:
logger.info("{} records processed".format(
report.counters["record_counter"]))
n_ev_strings_per_record = 0
clinvar_record = clinvar.ClinvarRecord(cellbase_record['clinvarSet'])
for clinvar_record_measure in clinvar_record.measures:
report.counters["n_nsvs"] += (clinvar_record_measure.nsv_id
is not None)
append_nsv(report.nsv_list, clinvar_record_measure)
report.counters["n_multiple_allele_origin"] += (len(
clinvar_record.allele_origins) > 1)
traits = create_traits(clinvar_record.traits, mappings.trait_2_efo,
report)
converted_allele_origins = convert_allele_origins(
clinvar_record.allele_origins)
for consequence_type, trait, allele_origin in itertools.product(
get_consequence_types(clinvar_record_measure,
mappings.consequence_type_dict),
traits, converted_allele_origins):
if skip_record(clinvar_record, clinvar_record_measure,
consequence_type, allele_origin,
allowed_clinical_significance, report):
continue
if allele_origin == 'germline':
evidence_string = evidence_strings.CTTVGeneticsEvidenceString(
clinvar_record, clinvar_record_measure, report, trait,
consequence_type)
elif allele_origin == 'somatic':
evidence_string = evidence_strings.CTTVSomaticEvidenceString(
clinvar_record, clinvar_record_measure, report, trait,
consequence_type)
else:
raise AssertionError(
'Unknown allele_origin present in the data: {}'.format(
allele_origin))
# Validate and immediately output the evidence string (not keeping everything in memory)
validate_evidence_string(evidence_string, clinvar_record,
trait,
consequence_type.ensembl_gene_id,
ot_schema_contents)
output_evidence_strings_file.write(
json.dumps(evidence_string) + '\n')
report.evidence_string_count += 1
report.evidence_list.append([
clinvar_record.accession, clinvar_record_measure.rs_id,
trait.clinvar_name, trait.ontology_id
])
report.counters["n_valid_rs_and_nsv"] += (
clinvar_record_measure.nsv_id is not None)
report.traits.add(trait.ontology_id)
report.remove_trait_mapping(trait.clinvar_name)
report.ensembl_gene_id_uris.add(
evidence_strings.get_ensembl_gene_id_uri(
consequence_type.ensembl_gene_id))
n_ev_strings_per_record += 1
if n_ev_strings_per_record > 0:
report.counters["n_processed_clinvar_records"] += 1
if n_ev_strings_per_record > 1:
report.counters["n_multiple_evidence_strings"] += 1
output_evidence_strings_file.close()
return report