class LookUp(object):
def __init__(self):
self.blw = BioLinkWrapper(Config().get_biolink_api_endpoint())
self.mg = get_client('gene')
self.input_object = ''
self.meta = {
'data_type': 'disease',
'input_type': {
'complexity': 'single',
'id_type': ['MONDO', 'DO', 'OMIM'],
},
'output_type': {
'complexity': 'set',
'id_type': 'HGNC'
},
'taxon': 'human',
'limit': None,
'source': 'Monarch Biolink',
'predicate': 'blm:gene associated with condition'
}
def metadata(self):
print("""Mod O DiseaseGeneLookup metadata:""")
pprint(self.meta)
#
# def load_input_object(self, input_object):
# input_object = self.blw.get_obj(obj_id=input_object['input'])
# self.input_object = {
# 'id': input_object['id'],
# 'label': input_object['label'],
# 'description': input_object['description'],
# }
#
# def get_input_object_id(self):
# return self.input_object['id']
def echo_input_object(self, output=None):
if output:
dump(self.input_object, output, indent=4, separators=(',', ': '))
else:
dump(self.input_object, stdout, indent=4, separators=(',', ': '))
def disease_geneset_lookup(self, name, id):
input_disease_label = name
input_disease_id = id
input_gene_set = self.blw.disease2genes(input_disease_id)
input_gene_set = [self.blw.parse_association(input_disease_id, input_disease_label, x) for x in
input_gene_set['associations']]
for input_gene in input_gene_set:
igene_mg = self.mg.query(input_gene['hit_id'].replace('HGNC', 'hgnc'), species='human', entrezonly=True,
fields='entrez,HGNC,symbol')
input_gene.update({'input_ncbi': 'NCBIGene:{}'.format(igene_mg['hits'][0]['_id'])})
input_genes_df = pd.DataFrame(data=input_gene_set)
# # group duplicate ids and gather sources
input_genes_df['sources'] = input_genes_df['sources'].str.join(', ')
input_genes_df = input_genes_df.groupby(
['input_id', 'input_symbol', 'hit_id', 'hit_symbol', 'relation'])['sources'].apply(', '.join).reset_index()
return input_genes_df
class LookUp(object):
def __init__(self):
self.blw = BioLinkWrapper()
self.mg = MyGeneInfo()
self.input_object = ''
self.meta = {
'data_type': 'disease',
'input_type': {
'complexity': 'single',
'id_type': ['MONDO', 'DO', 'OMIM'],
},
'output_type': {
'complexity': 'set',
'id_type': 'HGNC'
},
'taxon': 'human',
'limit': None,
'source': 'Monarch Biolink',
'predicate': 'blm:gene associated with condition'
}
print("""Mod O DiseaseGeneLookup metadata:""")
pprint(self.meta)
def load_input_object(self, input_object):
input_object = self.blw.get_obj(obj_id=input_object['input'])
self.input_object = {
'id': input_object['id'],
'label': input_object['label'],
'description': input_object['description'],
}
pprint(self.input_object)
def disease_geneset_lookup(self):
input_disease_id = self.input_object['id']
input_disease_label = self.input_object['label']
input_gene_set = self.blw.disease2genes(input_disease_id)
input_gene_set = [
self.blw.parse_association(input_disease_id, input_disease_label,
x)
for x in input_gene_set['associations']
]
# for input_gene in input_gene_set:
# igene_mg = self.mg.query(input_gene['hit_id'].replace('HGNC', 'hgnc'), species='human', entrezonly=True,
# fields='entrez,HGNC,symbol')
# input_gene.update({'input_ncbi': 'NCBIGene:{}'.format(igene_mg['hits'][0]['_id'])})
input_genes_df = pd.DataFrame(data=input_gene_set)
# # group duplicate ids and gather sources
input_genes_df['sources'] = input_genes_df['sources'].str.join(', ')
input_genes_df = input_genes_df.groupby(
['input_id', 'input_symbol', 'hit_id', 'hit_symbol',
'relation'])['sources'].apply(', '.join).reset_index()
return input_genes_df