def _process_result(variant_json, saved_variant):
if add_tags:
variant_json.update({
'tags': [
get_json_for_variant_tag(tag)
for tag in saved_variant.varianttag_set.all()
],
'functionalData': [
get_json_for_variant_functional_data(tag)
for tag in saved_variant.variantfunctionaldata_set.all()
],
'notes': [
get_json_for_variant_note(tag)
for tag in saved_variant.variantnote_set.all()
],
})
if add_details:
saved_variant_json = json.loads(saved_variant.saved_variant_json
or '{}')
variant_json.update(
variant_details(saved_variant_json, project
or saved_variant.project, user, **kwargs))
variant_json.update({
'variantId': saved_variant.guid, # TODO get from json
'familyGuids': [saved_variant.family.guid],
})
return variant_json
def _process_result(variant_json, saved_variant):
if add_tags:
variant_json.update({
'tags': [get_json_for_variant_tag(tag) for tag in saved_variant.varianttag_set.all()],
'functionalData': [get_json_for_variant_functional_data(tag) for tag in
saved_variant.variantfunctionaldata_set.all()],
'notes': [get_json_for_variant_note(tag) for tag in saved_variant.variantnote_set.all()],
})
if add_details:
saved_variant_json = json.loads(saved_variant.saved_variant_json or '{}')
variant_json.update(variant_details(saved_variant_json, project or saved_variant.project, user, **kwargs))
variant_json.update({
'variantId': saved_variant.guid, # TODO get from json
'familyGuids': [saved_variant.family.guid],
})
return variant_json
def _generate_rows(project, loaded_samples_by_project_family,
saved_variants_by_project_family, errors):
rows = []
loaded_samples_by_family = loaded_samples_by_project_family[project.guid]
saved_variants_by_family = saved_variants_by_project_family[project.guid]
if not loaded_samples_by_family:
errors.append("No data loaded for project: %s" % project)
logger.info("No data loaded for project: %s" % project)
return []
if "external" in project.name or "reprocessed" in project.name:
sequencing_approach = "REAN"
else:
sequencing_approach = loaded_samples_by_family.values(
)[0][-1].sample_type
now = timezone.now()
for family in project.families:
samples = loaded_samples_by_family.get(family.guid)
if not samples:
errors.append("No data loaded for family: %s. Skipping..." %
family)
continue
row = {
"project_guid":
project.guid,
"family_guid":
family.guid,
"family_id":
family.family_id,
"collaborator":
project.name,
"sequencing_approach":
sequencing_approach,
"extras_pedigree_url":
family.pedigree_image.url if family.pedigree_image else "",
"coded_phenotype":
family.coded_phenotype or "",
"analysis_summary": (family.analysis_summary or '').strip('" \n'),
}
row.update(DEFAULT_ROW)
t0 = samples[0].loaded_date
t0_diff = rdelta.relativedelta(now, t0)
t0_months_since_t0 = t0_diff.years * 12 + t0_diff.months
row.update({
"t0": t0,
"t0_copy": t0,
"months_since_t0": t0_months_since_t0,
})
if t0_months_since_t0 < 12:
row['analysis_complete_status'] = "first_pass_in_progress"
submitted_to_mme = SEQR_ID_TO_MME_ID_MAP.find_one({
'project_id':
project.deprecated_project_id,
'family_id':
family.family_id
})
if submitted_to_mme:
row["submitted_to_mme"] = "Y"
phenotips_individual_data_records = [
json.loads(i.phenotips_data) for i in family.individual_set.all()
if i.phenotips_data
]
phenotips_individual_expected_inheritance_model = [
inheritance_mode["label"]
for phenotips_data in phenotips_individual_data_records
for inheritance_mode in phenotips_data.get(
"global_mode_of_inheritance", [])
]
if len(phenotips_individual_expected_inheritance_model) == 1:
row["expected_inheritance_model"] = phenotips_individual_expected_inheritance_model.pop(
)
phenotips_individual_mim_disorders = [
phenotips_data.get("disorders", [])
for phenotips_data in phenotips_individual_data_records
]
omim_number_initial = next(
(disorder["id"] for disorders in phenotips_individual_mim_disorders
for disorder in disorders if "id" in disorder),
'').replace("MIM:", "")
if omim_number_initial:
row.update({
"omim_number_initial": omim_number_initial,
"phenotype_class": "Known",
})
if family.post_discovery_omim_number:
row["omim_number_post_discovery"] = family.post_discovery_omim_number
phenotips_individual_features = [
phenotips_data.get("features", [])
for phenotips_data in phenotips_individual_data_records
]
category_not_set_on_some_features = False
for features_list in phenotips_individual_features:
for feature in features_list:
if "category" not in feature:
category_not_set_on_some_features = True
continue
if feature["observed"].lower() == "yes":
hpo_category_id = feature["category"]
hpo_category_name = HPO_CATEGORY_NAMES[hpo_category_id]
key = hpo_category_name.lower().replace(" ", "_").replace(
"/", "_")
row[key] = "Y"
elif feature["observed"].lower() == "no":
continue
else:
raise ValueError("Unexpected value for 'observed' in %s" %
(feature, ))
if category_not_set_on_some_features:
errors.append(
"HPO category field not set for some HPO terms in %s" % family)
saved_variants = saved_variants_by_family.get(family.guid)
if not saved_variants:
rows.append(row)
continue
saved_variants_to_json = {}
for variant in saved_variants:
if not variant.saved_variant_json:
errors.append("%s - variant annotation not found" % variant)
rows.append(row)
continue
saved_variant_json = variant_details(json.loads(
variant.saved_variant_json),
project,
user=None)
if not saved_variant_json['transcripts']:
errors.append("%s - no gene ids" % variant)
rows.append(row)
continue
saved_variants_to_json[variant] = saved_variant_json
affected_sample_guids = set()
unaffected_sample_guids = set()
for sample in samples:
if sample.individual.affected == "A":
affected_sample_guids.add(sample.guid)
elif sample.individual.affected == "N":
unaffected_sample_guids.add(sample.guid)
potential_compound_het_genes = defaultdict(set)
for variant, saved_variant_json in saved_variants_to_json.items():
inheritance_models = set()
affected_indivs_with_hom_alt_variants = set()
affected_indivs_with_het_variants = set()
unaffected_indivs_with_hom_alt_variants = set()
unaffected_indivs_with_het_variants = set()
is_x_linked = False
genotypes = saved_variant_json.get('genotypes')
if genotypes:
chrom = saved_variant_json['chrom']
is_x_linked = "X" in chrom
for sample_guid, genotype in genotypes.items():
if genotype[
"numAlt"] == 2 and sample_guid in affected_sample_guids:
affected_indivs_with_hom_alt_variants.add(sample_guid)
elif genotype[
"numAlt"] == 1 and sample_guid in affected_sample_guids:
affected_indivs_with_het_variants.add(sample_guid)
elif genotype[
"numAlt"] == 2 and sample_guid in unaffected_sample_guids:
unaffected_indivs_with_hom_alt_variants.add(
sample_guid)
elif genotype[
"numAlt"] == 1 and sample_guid in unaffected_sample_guids:
unaffected_indivs_with_het_variants.add(sample_guid)
# AR-homozygote, AR-comphet, AR, AD, de novo, X-linked, UPD, other, multiple
if not unaffected_indivs_with_hom_alt_variants and affected_indivs_with_hom_alt_variants:
if is_x_linked:
inheritance_models.add("X-linked")
else:
inheritance_models.add("AR-homozygote")
if not unaffected_indivs_with_hom_alt_variants and not unaffected_indivs_with_het_variants and affected_indivs_with_het_variants:
if unaffected_sample_guids:
inheritance_models.add("de novo")
else:
inheritance_models.add("AD")
if not unaffected_indivs_with_hom_alt_variants and (
len(unaffected_sample_guids) < 2
or unaffected_indivs_with_het_variants
) and affected_indivs_with_het_variants and not affected_indivs_with_hom_alt_variants:
for gene_id in saved_variant_json['transcripts']:
potential_compound_het_genes[gene_id].add(variant)
saved_variant_json['inheritance'] = inheritance_models
gene_ids_to_saved_variants = defaultdict(set)
gene_ids_to_variant_tag_names = defaultdict(set)
gene_ids_to_inheritance = defaultdict(set)
# Compound het variants are reported in the gene that they share
for gene_id, variants in potential_compound_het_genes.items():
if len(variants) > 1:
gene_ids_to_inheritance[gene_id].add("AR-comphet")
# Only include compound hets for one of the genes they are both in
existing_gene_id = next(
(existing_gene_id for existing_gene_id, existing_variants
in gene_ids_to_saved_variants.items()
if existing_variants == variants), None)
if existing_gene_id:
main_gene_ids = {
saved_variants_to_json[variant]['mainTranscript']
['geneId']
for variant in variants
}
if gene_id in main_gene_ids:
gene_ids_to_saved_variants[
gene_id] = gene_ids_to_saved_variants[
existing_gene_id]
del gene_ids_to_saved_variants[existing_gene_id]
gene_ids_to_variant_tag_names[
gene_id] = gene_ids_to_variant_tag_names[
existing_gene_id]
del gene_ids_to_variant_tag_names[existing_gene_id]
else:
for variant in variants:
saved_variants_to_json[variant]['inheritance'] = {
"AR-comphet"
}
gene_ids_to_variant_tag_names[gene_id].update({
vt.variant_tag_type.name
for vt in variant.discovery_tags
})
gene_ids_to_saved_variants[gene_id].update(variants)
# Non-compound het variants are reported in the main transcript gene
for variant, saved_variant_json in saved_variants_to_json.items():
if "AR-comphet" not in saved_variant_json['inheritance']:
gene_id = saved_variant_json['mainTranscript']['geneId']
gene_ids_to_saved_variants[gene_id].add(variant)
gene_ids_to_variant_tag_names[gene_id].update({
vt.variant_tag_type.name
for vt in variant.discovery_tags
})
gene_ids_to_inheritance[gene_id].update(
saved_variant_json['inheritance'])
if len(gene_ids_to_saved_variants) > 1:
row["gene_count"] = len(gene_ids_to_saved_variants)
for gene_id, variants in gene_ids_to_saved_variants.items():
# create a copy of the row dict
row = dict(row)
row["actual_inheritance_model"] = ", ".join(
gene_ids_to_inheritance[gene_id])
row["gene_id"] = gene_id
variant_tag_names = gene_ids_to_variant_tag_names[gene_id]
has_tier1 = any(
name.startswith("Tier 1") for name in variant_tag_names)
has_tier2 = any(
name.startswith("Tier 2") for name in variant_tag_names)
has_known_gene_for_phenotype = 'Known gene for phenotype' in variant_tag_names
row.update({
"solved": ("TIER 1 GENE" if
(has_tier1 or has_known_gene_for_phenotype) else
("TIER 2 GENE" if has_tier2 else "N")),
"komp_early_release":
"Y" if 'Share with KOMP' in variant_tag_names else "N",
})
if has_tier1 or has_tier2 or has_known_gene_for_phenotype:
row.update({
"posted_publicly":
"",
"analysis_complete_status":
"complete",
"novel_mendelian_gene":
"Y" if any("Novel gene" in name
for name in variant_tag_names) else "N",
})
if any(tag in variant_tag_names for tag in [
'Tier 1 - Phenotype expansion',
'Tier 1 - Novel mode of inheritance',
'Tier 2 - Phenotype expansion',
]):
row["phenotype_class"] = "EXPAN"
elif any(tag in variant_tag_names for tag in [
'Tier 1 - Phenotype not delineated',
'Tier 2 - Phenotype not delineated'
]):
row["phenotype_class"] = "UE"
if not submitted_to_mme:
if has_tier1 or has_tier2:
row["submitted_to_mme"] = "N" if t0_months_since_t0 > 7 else "TBD"
elif has_known_gene_for_phenotype:
row["submitted_to_mme"] = "KPG"
if has_tier1 or has_tier2:
for functional_field in FUNCTIONAL_DATA_FIELD_MAP.values():
if functional_field == ADDITIONAL_KINDREDS_FIELD:
row[functional_field] = "1"
elif functional_field in METADATA_FUNCTIONAL_DATA_FIELDS:
row[functional_field] = "NA"
else:
row[functional_field] = "N"
elif has_known_gene_for_phenotype:
for functional_field in FUNCTIONAL_DATA_FIELD_MAP.values():
row[functional_field] = "KPG"
variant_tag_list = []
for variant in variants:
variant_id = "-".join(
map(
str,
list(get_chrom_pos(variant.xpos_start)) +
[variant.ref, variant.alt]))
variant_tag_list += [(variant_id, gene_id,
vt.variant_tag_type.name.lower())
for vt in variant.discovery_tags]
for f in variant.variantfunctionaldata_set.all():
functional_field = FUNCTIONAL_DATA_FIELD_MAP[
f.functional_data_tag]
if functional_field in METADATA_FUNCTIONAL_DATA_FIELDS:
value = f.metadata
if functional_field == ADDITIONAL_KINDREDS_FIELD:
value = str(int(value) + 1)
elif row[functional_field] != 'NS':
value = '{} {}'.format(row[functional_field],
value)
else:
value = 'Y'
row[functional_field] = value
row["extras_variant_tag_list"] = variant_tag_list
rows.append(row)
_update_gene_symbols(rows)
_update_initial_omim_numbers(rows)
return rows
def _generate_rows(project, loaded_samples_by_project_family, saved_variants_by_project_family, errors):
rows = []
loaded_samples_by_family = loaded_samples_by_project_family[project.guid]
saved_variants_by_family = saved_variants_by_project_family[project.guid]
if not loaded_samples_by_family:
errors.append("No data loaded for project: %s" % project)
logger.info("No data loaded for project: %s" % project)
return []
if "external" in project.name or "reprocessed" in project.name:
sequencing_approach = "REAN"
else:
sequencing_approach = loaded_samples_by_family.values()[0][-1].sample_type
now = timezone.now()
for family in project.families:
samples = loaded_samples_by_family.get(family.guid)
if not samples:
errors.append("No data loaded for family: %s. Skipping..." % family)
continue
row = {
"project_guid": project.guid,
"family_guid": family.guid,
"family_id": family.family_id,
"collaborator": project.name,
"sequencing_approach": sequencing_approach,
"extras_pedigree_url": family.pedigree_image.url if family.pedigree_image else "",
"coded_phenotype": family.coded_phenotype or "",
"pubmed_ids": '; '.join(family.pubmed_ids),
"analysis_summary": (family.analysis_summary or '').strip('" \n'),
"row_id": family.guid,
"num_individuals_sequenced": len({sample.individual for sample in samples})
}
row.update(DEFAULT_ROW)
t0 = samples[0].loaded_date
t0_diff = rdelta.relativedelta(now, t0)
t0_months_since_t0 = t0_diff.years * 12 + t0_diff.months
row.update({
"t0": t0,
"t0_copy": t0,
"months_since_t0": t0_months_since_t0,
})
if t0_months_since_t0 < 12:
row['analysis_complete_status'] = "first_pass_in_progress"
submitted_to_mme = any(i.mme_submitted_date for i in family.individual_set.all())
if submitted_to_mme:
row["submitted_to_mme"] = "Y"
phenotips_individual_data_records = [json.loads(i.phenotips_data) for i in family.individual_set.all() if i.phenotips_data]
phenotips_individual_expected_inheritance_model = [
inheritance_mode["label"] for phenotips_data in phenotips_individual_data_records for inheritance_mode in phenotips_data.get("global_mode_of_inheritance", [])
]
if len(phenotips_individual_expected_inheritance_model) == 1:
row["expected_inheritance_model"] = phenotips_individual_expected_inheritance_model.pop()
phenotips_individual_mim_disorders = [phenotips_data.get("disorders", []) for phenotips_data in phenotips_individual_data_records]
omim_number_initial = next((disorder["id"] for disorders in phenotips_individual_mim_disorders for disorder in disorders if "id" in disorder), '').replace("MIM:", "")
if omim_number_initial:
row.update({
"omim_number_initial": omim_number_initial,
"phenotype_class": "KNOWN",
})
if family.post_discovery_omim_number:
row["omim_number_post_discovery"] = family.post_discovery_omim_number
phenotips_individual_features = [phenotips_data.get("features", []) for phenotips_data in phenotips_individual_data_records]
category_not_set_on_some_features = False
for features_list in phenotips_individual_features:
for feature in features_list:
if "category" not in feature:
category_not_set_on_some_features = True
continue
if feature["observed"].lower() == "yes":
hpo_category_id = feature["category"]
hpo_category_name = HPO_CATEGORY_NAMES[hpo_category_id]
key = hpo_category_name.lower().replace(" ", "_").replace("/", "_")
row[key] = "Y"
elif feature["observed"].lower() == "no":
continue
else:
raise ValueError("Unexpected value for 'observed' in %s" % (feature,))
if category_not_set_on_some_features:
errors.append("HPO category field not set for some HPO terms in %s" % family)
saved_variants = saved_variants_by_family.get(family.guid)
if not saved_variants:
rows.append(row)
continue
saved_variants_to_json = {}
for variant in saved_variants:
if not variant.saved_variant_json:
errors.append("%s - variant annotation not found" % variant)
rows.append(row)
continue
saved_variant_json = variant_details(json.loads(variant.saved_variant_json), project, user=None)
if not saved_variant_json['transcripts']:
errors.append("%s - no gene ids" % variant)
rows.append(row)
continue
saved_variants_to_json[variant] = saved_variant_json
affected_individual_guids = set()
unaffected_individual_guids = set()
for sample in samples:
if sample.individual.affected == "A":
affected_individual_guids.add(sample.individual.guid)
elif sample.individual.affected == "N":
unaffected_individual_guids.add(sample.individual.guid)
potential_compound_het_genes = defaultdict(set)
for variant, saved_variant_json in saved_variants_to_json.items():
inheritance_models = set()
affected_indivs_with_hom_alt_variants = set()
affected_indivs_with_het_variants = set()
unaffected_indivs_with_hom_alt_variants = set()
unaffected_indivs_with_het_variants = set()
is_x_linked = False
genotypes = saved_variant_json.get('genotypes')
if genotypes:
chrom = saved_variant_json['chrom']
is_x_linked = "X" in chrom
for sample_guid, genotype in genotypes.items():
if genotype["numAlt"] == 2 and sample_guid in affected_individual_guids:
affected_indivs_with_hom_alt_variants.add(sample_guid)
elif genotype["numAlt"] == 1 and sample_guid in affected_individual_guids:
affected_indivs_with_het_variants.add(sample_guid)
elif genotype["numAlt"] == 2 and sample_guid in unaffected_individual_guids:
unaffected_indivs_with_hom_alt_variants.add(sample_guid)
elif genotype["numAlt"] == 1 and sample_guid in unaffected_individual_guids:
unaffected_indivs_with_het_variants.add(sample_guid)
# AR-homozygote, AR-comphet, AR, AD, de novo, X-linked, UPD, other, multiple
if not unaffected_indivs_with_hom_alt_variants and affected_indivs_with_hom_alt_variants:
if is_x_linked:
inheritance_models.add("X-linked")
else:
inheritance_models.add("AR-homozygote")
if not unaffected_indivs_with_hom_alt_variants and not unaffected_indivs_with_het_variants and affected_indivs_with_het_variants:
if unaffected_individual_guids:
inheritance_models.add("de novo")
else:
inheritance_models.add("AD")
if not unaffected_indivs_with_hom_alt_variants and (len(
unaffected_individual_guids) < 2 or unaffected_indivs_with_het_variants) and affected_indivs_with_het_variants and not affected_indivs_with_hom_alt_variants:
for gene_id in saved_variant_json['transcripts']:
potential_compound_het_genes[gene_id].add(variant)
saved_variant_json['inheritance'] = inheritance_models
gene_ids_to_saved_variants = defaultdict(set)
gene_ids_to_variant_tag_names = defaultdict(set)
gene_ids_to_inheritance = defaultdict(set)
# Compound het variants are reported in the gene that they share
for gene_id, variants in potential_compound_het_genes.items():
if len(variants) > 1:
gene_ids_to_inheritance[gene_id].add("AR-comphet")
# Only include compound hets for one of the genes they are both in
existing_gene_id = next((
existing_gene_id for existing_gene_id, existing_variants in gene_ids_to_saved_variants.items()
if existing_variants == variants), None)
if existing_gene_id:
main_gene_ids = {
saved_variants_to_json[variant]['mainTranscript']['geneId'] for variant in variants
}
if gene_id in main_gene_ids:
gene_ids_to_saved_variants[gene_id] = gene_ids_to_saved_variants[existing_gene_id]
del gene_ids_to_saved_variants[existing_gene_id]
gene_ids_to_variant_tag_names[gene_id] = gene_ids_to_variant_tag_names[existing_gene_id]
del gene_ids_to_variant_tag_names[existing_gene_id]
else:
for variant in variants:
saved_variants_to_json[variant]['inheritance'] = {"AR-comphet"}
gene_ids_to_variant_tag_names[gene_id].update(
{vt.variant_tag_type.name for vt in variant.discovery_tags})
gene_ids_to_saved_variants[gene_id].update(variants)
# Non-compound het variants are reported in the main transcript gene
for variant, saved_variant_json in saved_variants_to_json.items():
if "AR-comphet" not in saved_variant_json['inheritance']:
gene_id = saved_variant_json['mainTranscript']['geneId']
gene_ids_to_saved_variants[gene_id].add(variant)
gene_ids_to_variant_tag_names[gene_id].update({vt.variant_tag_type.name for vt in variant.discovery_tags})
gene_ids_to_inheritance[gene_id].update(saved_variant_json['inheritance'])
if len(gene_ids_to_saved_variants) > 1:
row["gene_count"] = len(gene_ids_to_saved_variants)
for gene_id, variants in gene_ids_to_saved_variants.items():
# create a copy of the row dict
row = dict(row)
row["actual_inheritance_model"] = ", ".join(gene_ids_to_inheritance[gene_id])
row["gene_id"] = gene_id
row["row_id"] += gene_id
variant_tag_names = gene_ids_to_variant_tag_names[gene_id]
has_tier1 = any(name.startswith("Tier 1") for name in variant_tag_names)
has_tier2 = any(name.startswith("Tier 2") for name in variant_tag_names)
has_known_gene_for_phenotype = 'Known gene for phenotype' in variant_tag_names
row.update({
"solved": ("TIER 1 GENE" if (has_tier1 or has_known_gene_for_phenotype) else (
"TIER 2 GENE" if has_tier2 else "N")),
"komp_early_release": "Y" if 'Share with KOMP' in variant_tag_names else "N",
})
if has_tier1 or has_tier2 or has_known_gene_for_phenotype:
row.update({
"posted_publicly": "",
"analysis_complete_status": "complete",
"novel_mendelian_gene": "Y" if any("Novel gene" in name for name in variant_tag_names) else "N",
})
if has_known_gene_for_phenotype:
row["phenotype_class"] = "KNOWN"
elif any(tag in variant_tag_names for tag in [
'Tier 1 - Known gene, new phenotype', 'Tier 2 - Known gene, new phenotype',
]):
row["phenotype_class"] = "NEW"
elif any(tag in variant_tag_names for tag in [
'Tier 1 - Phenotype expansion', 'Tier 1 - Novel mode of inheritance', 'Tier 2 - Phenotype expansion',
]):
row["phenotype_class"] = "EXPAN"
elif any(tag in variant_tag_names for tag in [
'Tier 1 - Phenotype not delineated', 'Tier 2 - Phenotype not delineated'
]):
row["phenotype_class"] = "UE"
if not submitted_to_mme:
if has_tier1 or has_tier2:
row["submitted_to_mme"] = "N" if t0_months_since_t0 > 7 else "TBD"
elif has_known_gene_for_phenotype:
row["submitted_to_mme"] = "KPG"
if has_tier1 or has_tier2:
# Set defaults
for functional_field in FUNCTIONAL_DATA_FIELD_MAP.values():
if functional_field == ADDITIONAL_KINDREDS_FIELD:
row[functional_field] = "1"
elif functional_field in METADATA_FUNCTIONAL_DATA_FIELDS:
row[functional_field] = "NA"
else:
row[functional_field] = "N"
# Set values
for variant in variants:
for f in variant.variantfunctionaldata_set.all():
functional_field = FUNCTIONAL_DATA_FIELD_MAP[f.functional_data_tag]
if functional_field in METADATA_FUNCTIONAL_DATA_FIELDS:
value = f.metadata
if functional_field == ADDITIONAL_KINDREDS_FIELD:
value = str(int(value) + 1)
elif functional_field == OVERLAPPING_KINDREDS_FIELD:
existing_val = row[functional_field]
if existing_val != 'NA':
value = str(max(int(existing_val), int(value)))
elif row[functional_field] != 'NS':
value = '{} {}'.format(row[functional_field], value)
else:
value = 'Y'
row[functional_field] = value
elif has_known_gene_for_phenotype:
for functional_field in FUNCTIONAL_DATA_FIELD_MAP.values():
row[functional_field] = "KPG"
row["extras_variant_tag_list"] = []
for variant in variants:
variant_id = "-".join(map(str, list(get_chrom_pos(variant.xpos_start)) + [variant.ref, variant.alt]))
row["extras_variant_tag_list"] += [
(variant_id, gene_id, vt.variant_tag_type.name.lower()) for vt in variant.discovery_tags
]
rows.append(row)
_update_gene_symbols(rows)
_update_initial_omim_numbers(rows)
return rows