def preload_ontologies():
ontologies = settings.get_biolink_config().get('ontologies')
for ontology in ontologies:
handle = ontology['handle']
if ontology['pre_load']:
log.info("Loading {}".format(ontology['id']))
get_ontology(handle)
def get(self):
"""
For a given gene(s), summarize its annotations over a defined set of slim
"""
args = self.function_parser.parse_args()
slim = args.get('slim')
del args['slim']
subjects = args.get('subject')
del args['subject']
# Note that GO currently uses UniProt as primary ID for some sources: https://github.com/biolink/biolink-api/issues/66
# https://github.com/monarch-initiative/dipper/issues/461
sg_dev = SciGraph(get_biolink_config()['scigraph_data']['url'])
subjects = [
x.replace('WormBase:', 'WB:') if 'WormBase:' in x else x
for x in subjects
]
slimmer_subjects = []
for s in subjects:
if 'HGNC:' in s or 'NCBIGene:' in s or 'ENSEMBL:' in s:
prots = identifier_converter.convert_gene_to_protein(s)
if len(prots) == 0:
prots = [s]
slimmer_subjects += prots
else:
slimmer_subjects.append(s)
results = map2slim(subjects=slimmer_subjects,
slim=slim,
object_category='function',
user_agent=USER_AGENT,
**args)
# To the fullest extent possible return HGNC ids
checked = {}
for result in results:
for association in result['assocs']:
taxon = association['subject']['taxon']['id']
proteinId = association['subject']['id']
if taxon == 'NCBITaxon:9606' and proteinId.startswith(
'UniProtKB:'):
if proteinId not in checked:
genes = identifier_converter.convert_protein_to_gene(
proteinId)
for gene in genes:
if gene.startswith('HGNC'):
association['subject']['id'] = gene
checked[proteinId] = gene
else:
association['subject']['id'] = checked[proteinId]
return results
def __init__(self):
self.scigraph = SciGraph(get_biolink_config()['scigraph_data']['url'])
import logging
from flask import request
from flask_restplus import Resource, inputs
from biolink.datamodel.serializers import bbop_graph, bio_object
from biolink.error_handlers import NoResultFoundException, UnhandledException
from scigraph.scigraph_util import SciGraph
from scigraph.model.BBOPGraph import BBOPGraph
from biolink.api.restplus import api
from biolink.settings import get_biolink_config
log = logging.getLogger(__name__)
sg_data = SciGraph(get_biolink_config()['scigraph_data']['url'])
sg_ont = SciGraph(get_biolink_config()['scigraph_ontology']['url'])
@api.doc(params={'id': 'CURIE e.g. HP:0000465'})
class NodeResource(Resource):
@api.marshal_list_with(bio_object)
def get(self, id):
"""
Returns a graph node.
A node is an abstract representation of some kind of entity. The entity may be a physical thing such as a patient,
a molecular entity such as a gene or protein, or a conceptual entity such as a class from an ontology.
"""
graph = sg_data.bioobject(id)
return graph
import logging
from flask import request
from flask_restplus import Resource, inputs
from biolink.datamodel.serializers import association, bbop_graph, bio_object
from biolink.error_handlers import NoResultFoundException
from scigraph.scigraph_util import SciGraph
from scigraph.model.BBOPGraph import BBOPGraph
from biolink.api.restplus import api
from biolink.settings import get_biolink_config
log = logging.getLogger(__name__)
sg = SciGraph(get_biolink_config()['scigraph_data']['url'])
@api.doc(params={'id': 'CURIE e.g. HP:0000465'})
class NodeResource(Resource):
@api.marshal_list_with(bio_object)
def get(self, id):
"""
Returns a graph node.
A node is an abstract representation of some kind of entity. The entity may be a physical thing such as a patient,
a molecular entity such as a gene or protein, or a conceptual entity such as a class from an ontology.
"""
graph = sg.bioobject(id)
return graph
@api.doc(params={'id': 'CURIE e.g. HP:0000465'})
import logging
from ontobio.ontol_factory import OntologyFactory
from biolink.settings import get_biolink_config
cfg = get_biolink_config()
omap = {}
def get_ontology(id):
handle = id
for c in cfg['ontologies']:
if c['id'] == id:
logging.info("getting handle for id: {} from cfg".format(id))
handle = c['handle']
if handle not in omap:
logging.info("Creating a new ontology object for {}".format(handle))
ofa = OntologyFactory()
omap[handle] = ofa.create(handle)
else:
logging.info("Using cached for {}".format(handle))
return omap[handle]
default=False,
help='Should only the longest entity be returned for an overlapping group')
parser.add_argument('include_abbreviation',
type=inputs.boolean,
default=False,
help='Should abbreviations be included')
parser.add_argument('include_acronym',
type=inputs.boolean,
default=False,
help='Should acronyms be included')
parser.add_argument('include_numbers',
type=inputs.boolean,
default=False,
help='Should numbers be included')
scigraph = SciGraph(get_biolink_config()['scigraph_ontology']['url'])
def parse_args_for_annotator(parser):
"""
Convenience method for parsing and preparing parameters for SciGraph annotator
"""
args = parser.parse_args()
if 'include_category' in args:
val = args.pop('include_category')
args['includeCat'] = val
if 'exclude_category' in args:
val = args.pop('exclude_category')
args['excludeCat'] = val
if 'min_length' in args:
val = args.pop('min_length')
