def _add_component_pathway_association(self, gene_curie, pathway_curie,
pathway_label, eco_curie):
pathway = Pathway(self.graph)
pathway.addPathway(pathway_curie, pathway_label)
pathway.addComponentToPathway(gene_curie, pathway_curie)
association = Assoc(self.graph, self.name)
association.sub = gene_curie
association.rel = self.globaltt['involved in']
association.obj = pathway_curie
association.set_association_id()
association.add_evidence(eco_curie)
association.add_association_to_graph()
def _add_component_pathway_association(
self, eco_map, component, component_prefix, pathway_id,
pathway_prefix, pathway_label, go_ecode):
pathway = Pathway(self.graph)
pathway_curie = "{}:{}".format(pathway_prefix, pathway_id)
gene_curie = "{}:{}".format(component_prefix, component.strip())
eco_curie = eco_map[go_ecode]
pathway.addPathway(pathway_curie, pathway_label)
pathway.addComponentToPathway(gene_curie, pathway_curie)
association = Assoc(self.graph, self.name)
association.sub = gene_curie
association.rel = pathway.object_properties['involved_in']
association.obj = pathway_curie
association.set_association_id()
association.add_evidence(eco_curie)
association.add_association_to_graph()
return
def _add_component_pathway_association(
self, eco_map, component, component_prefix, pathway_id,
pathway_prefix, pathway_label, go_ecode):
pathway = Pathway(self.graph)
pathway_curie = "{}:{}".format(pathway_prefix, pathway_id)
gene_curie = "{}:{}".format(component_prefix, component.strip())
eco_curie = eco_map[go_ecode]
pathway.addPathway(pathway_curie, pathway_label)
pathway.addComponentToPathway(gene_curie, pathway_curie)
association = Assoc(self.graph, self.name)
association.sub = gene_curie
association.rel = self.globaltt['involved in']
association.obj = pathway_curie
association.set_association_id()
association.add_evidence(eco_curie)
association.add_association_to_graph()
return
def _parse_aeolus_data(self, document, or_limit=None):
model = Model(self.graph)
rxcui_curie = "RXCUI:{}".format(document['aeolus']['rxcui'])
uni_curie = "UNII:{}".format(document['aeolus']['unii'])
model.addLabel(rxcui_curie, document['aeolus']['drug_name'])
model.addLabel(uni_curie, document['aeolus']['drug_name'])
model.addSameIndividual(rxcui_curie, uni_curie)
self.graph.addTriple(rxcui_curie,
model.annotation_properties['inchi_key'],
document['unii']['inchikey'],
object_is_literal=True)
if or_limit is not None:
outcomes = (outcome for outcome in document['aeolus']['outcomes']
if 'ror' in outcome and outcome['ror'] >= or_limit)
else:
outcomes = (outcome for outcome in document['aeolus']['outcomes'])
for outcome in outcomes:
drug2outcome_assoc = Assoc(self.graph, self.name)
meddra_curie = "MEDDRA:{}".format(outcome['code'])
model.addLabel(meddra_curie, outcome['name'])
drug2outcome_assoc.sub = rxcui_curie
drug2outcome_assoc.obj = meddra_curie
drug2outcome_assoc.rel = Assoc.object_properties[
'causes_or_contributes']
drug2outcome_assoc.description = \
"A proportional reporting ratio or odds " \
"ratio greater than or equal to {} in the " \
"AEOLUS data was the significance cut-off " \
"used for creating drug-outcome associations".format(or_limit)
drug2outcome_assoc.add_association_to_graph()
drug2outcome_assoc.add_predicate_object(
Assoc.annotation_properties['probabalistic_quantifier'],
outcome['ror'], 'Literal')
self._add_outcome_evidence(drug2outcome_assoc.assoc_id, outcome)
self._add_outcome_provenance(drug2outcome_assoc.assoc_id, outcome)
def _add_gene_anatomy_association(self, gene_id, anatomy_curie, rank):
"""
:param gene_id: str Non curified ID
:param gene_label: str Gene symbol
:param anatomy_curie: str curified anatomy term
:param rank: str rank
:return: None
"""
g2a_association = Assoc(self.graph, self.name)
model = Model(self.graph)
gene_curie = "ENSEMBL:{}".format(gene_id)
rank = re.sub(r',', '', str(rank)) # ? can't do RE on a float ...
model.addIndividualToGraph(gene_curie, None)
g2a_association.sub = gene_curie
g2a_association.obj = anatomy_curie
g2a_association.rel = self.globaltt['expressed in']
g2a_association.add_association_to_graph()
g2a_association.add_predicate_object(
self.globaltt['has_quantifier'], float(rank), 'Literal', 'xsd:float')
def _add_gene_anatomy_association(self, gene_id, anatomy_curie, rank):
"""
:param gene_id: str Non curified ID
:param gene_label: str Gene symbol
:param anatomy_curie: str curified anatomy term
:param rank: str rank
:return: None
"""
g2a_association = Assoc(self.graph, self.name)
model = Model(self.graph)
gene_curie = "ENSEMBL:{}".format(gene_id)
rank = re.sub(r',', '', str(rank)) # ? can't do RE on a float ...
model.addIndividualToGraph(gene_curie, None)
g2a_association.sub = gene_curie
g2a_association.obj = anatomy_curie
g2a_association.rel = self.globaltt['expressed in']
g2a_association.add_association_to_graph()
g2a_association.add_predicate_object(
self.globaltt['has_quantifier'], float(rank), 'Literal', 'xsd:float')
return
def _parse_aeolus_data(self, document, or_limit=None):
model = Model(self.graph)
rxcui_curie = "RXCUI:{}".format(document['aeolus']['rxcui'])
uni_curie = "UNII:{}".format(document['aeolus']['unii'])
model.addLabel(rxcui_curie, document['aeolus']['drug_name'])
model.addLabel(uni_curie, document['aeolus']['drug_name'])
model.addSameIndividual(rxcui_curie, uni_curie)
self.graph.addTriple(
rxcui_curie, self.globaltt['inchi_key'], document['unii']['inchikey'],
object_is_literal=True)
if or_limit is not None:
outcomes = (outcome for outcome in document['aeolus']['outcomes']
if 'ror' in outcome and outcome['ror'] >= or_limit)
else:
outcomes = (outcome for outcome in document['aeolus']['outcomes'])
for outcome in outcomes:
drug2outcome_assoc = Assoc(self.graph, self.name)
meddra_curie = "MEDDRA:{}".format(outcome['code'])
model.addLabel(meddra_curie, outcome['name'])
drug2outcome_assoc.sub = rxcui_curie
drug2outcome_assoc.obj = meddra_curie
drug2outcome_assoc.rel = self.globaltt['causes_or_contributes']
drug2outcome_assoc.description = \
"A proportional reporting ratio or odds " \
"ratio greater than or equal to {} in the " \
"AEOLUS data was the significance cut-off " \
"used for creating drug-outcome associations".format(or_limit)
drug2outcome_assoc.add_association_to_graph()
drug2outcome_assoc.add_predicate_object(
self.globaltt['probabalistic_quantifier'], outcome['ror'], 'Literal')
self._add_outcome_evidence(drug2outcome_assoc.assoc_id, outcome)
self._add_outcome_provenance(drug2outcome_assoc.assoc_id, outcome)
def _add_gene_anatomy_association(self, gene_id, anatomy_curie, rank):
"""
:param gene_id: str Non curified ID
:param gene_label: str Gene symbol
:param anatomy_curie: str curified anatomy term
:param rank: str rank
:return: None
"""
g2a_association = Assoc(self.graph, self.name)
genotype = Genotype(self.graph)
model = Model(self.graph)
gene_curie = "ENSEMBL:{}".format(gene_id)
rank = re.sub(r',', '', rank)
model.addIndividualToGraph(ind_id=gene_curie, label=None,
ind_type=genotype.genoparts['gene'])
g2a_association.sub = gene_curie
g2a_association.obj = anatomy_curie
g2a_association.rel = Assoc.object_properties['expressed_in']
g2a_association.add_association_to_graph()
g2a_association.add_predicate_object(
Assoc.datatype_properties['has_quantifier'],
float(rank), 'Literal', 'xsd:float')
return