def yield_mouse_orthologs(hs_genes):
# map into mouse orthologs using biomart
query = B.new_query()
dataset = B.add_dataset(query, 'hsapiens_gene_ensembl')
B.add_attribute(dataset, 'ensembl_gene_id')
B.add_attribute(dataset, 'mouse_ensembl_gene')
filter = B.add_filter(dataset, name='ensembl_gene_id', value='')
filter.set('value', ','.join(ensembl_hs_genes))
for chunk in B.split_big_list(ensembl_hs_genes, 50):
#logging.info('Querying Ensembl biomart for chunk of %d genes', len(chunk))
filter.set('value', ','.join(chunk))
for row in B.yield_csv_query_results(query):
if row[1]:
yield row[1]
def yield_mouse_orthologs(hs_genes):
# map into mouse orthologs using biomart
query = B.new_query()
dataset = B.add_dataset(query, 'hsapiens_gene_ensembl')
B.add_attribute(dataset, 'ensembl_gene_id')
B.add_attribute(dataset, 'mouse_ensembl_gene')
filter = B.add_filter(dataset, name='ensembl_gene_id', value='')
filter.set('value', ','.join(ensembl_hs_genes))
for chunk in B.split_big_list(ensembl_hs_genes, 50):
#logging.info('Querying Ensembl biomart for chunk of %d genes', len(chunk))
filter.set('value', ','.join(chunk))
for row in B.yield_csv_query_results(query):
if row[1]:
yield row[1]
def get_ensembl_go_annotations(genes):
"@return: A map from the given genes to sets of go annotations."
import biopsy.identifiers.biomart as biomart
logging.info('Querying Ensembl biomart for GO annotations of %d genes', len(genes))
result = cookbook.DictOfLists()
for id_attr, evidence_attr in [
('go_biological_process_id', 'go_biological_process_linkage_type'),
('go_cellular_component_id', 'go_cellular_component_linkage_type'),
('go_molecular_function_id', 'go_molecular_function_linkage_type'),
]:
query = biomart.new_query()
dataset = biomart.add_dataset(query, 'mmusculus_gene_ensembl')
biomart.add_attribute(dataset, 'ensembl_gene_id')
biomart.add_attribute(dataset, id_attr)
biomart.add_attribute(dataset, evidence_attr)
filter = biomart.add_filter(dataset, name='ensembl_gene_id', value='')
for chunk in biomart.split_big_list((str(g) for g in genes), 50):
#logging.info('Querying Ensembl biomart for chunk of %d genes', len(chunk))
filter.set('value', ','.join(chunk))
for row in biomart.yield_csv_query_results(query):
if row[2] not in options.go_evidence_codes_to_ignore:
result[row[0]].append(row[1])
logging.info('Found %d go annotations', sum(len(v) for v in result.values()))
return result