for goterm in gene1:
sim1 = sim1 + self.__get_go_score(goterm, gene2)
sim2 = 0
for goterm in gene2:
sim2 = sim2 + self.__get_go_score(goterm, gene1)
score = (sim1 + sim2) / (len(gene1) + len(gene2))
return score
if __name__ == '__main__':
from oboio import OboIO
from src import download_go_graph
OBIO = OboIO()
ONTO = download_go_graph()
TERMS = OBIO.get_graph(ONTO)
# G-Sesame GO example
GSGO = GsesameGO(TERMS)
print 'GO:0043229 semantic value:', GSGO.semantic_value('GO:0043229')
print 'GO:0043231 semantic value:', GSGO.semantic_value('GO:0043231')
print 'Score for: GO:0043229 - GO:0043231:', \
GSGO.scores('GO:0043229', 'GO:0043231')
# G-Sesame Gene example
GSGENE = GsesameGene(TERMS)
GENE1 = [
'GO:0004022', 'GO:0004024', 'GO:0004174', 'GO:0046872', 'GO:0008270',
'GO:0004023'
]
GENE2 = [
sim1 = 0
for goterm in gene1:
sim1 = sim1 + self.__get_go_score(goterm, gene2)
sim2 = 0
for goterm in gene2:
sim2 = sim2 + self.__get_go_score(goterm, gene1)
score = (sim1 + sim2) / (len(gene1) + len(gene2))
return score
if __name__ == '__main__':
from oboio import OboIO
from src import download_go_graph
OBIO = OboIO()
ONTO = download_go_graph()
TERMS = OBIO.get_graph(ONTO)
# G-Sesame GO example
GSGO = GsesameGO(TERMS)
print 'GO:0043229 semantic value:', GSGO.semantic_value('GO:0043229')
print 'GO:0043231 semantic value:', GSGO.semantic_value('GO:0043231')
print 'Score for: GO:0043229 - GO:0043231:', \
GSGO.scores('GO:0043229', 'GO:0043231')
# G-Sesame Gene example
GSGENE = GsesameGene(TERMS)
GENE1 = ['GO:0004022', 'GO:0004024', 'GO:0004174', 'GO:0046872',
'GO:0008270', 'GO:0004023']
GENE2 = ['GO:0009055', 'GO:0005515', 'GO:0046872', 'GO:0008270',
'GO:0020037']
print 'Semantic similarities between the two genes:', \
path2 = golib.get_path(goterm2, pred=goterm2['id'], paths=[])
# We use goterm['id'] instead of the id provided to take into
# account alt_id which are in the list of goterms but not in the
# paths. Via goterm['id'] we get the 'normal' GO term identifier.
scores = self.__score_parents(goterm1['id'], goterm2['id'], path1,
path2)
if scores:
score = min(scores)
self.log.debug("%s and %s are parents" % (id1, id2))
return (score, score)
else:
score = self.__score_cousins(goterm1['id'], goterm2['id'], path1,
path2)
return score
if __name__ == '__main__':
from oboio import OboIO
GDC = GoDistanceCounter()
GOFILE = '../tests/test.obo'
OBIO = OboIO()
TERMS = OBIO.get_graph(GOFILE)
GDC = GoDistanceCounter(TERMS)
#gdc.get_biological_process()
#print "%s terms found in the biological process branch" % \
#len(self.biological_process.keys())
#outputfile = 'geneontology_biological_process-%s.obo' % \
#datetime.datetime.now().strftime('%Y%m%d')
#write_down_ontology(self.biological_process, outputfile)