def featureset_net_enr(meth,
feature_set_id=None,
p_value=None,
ref_wsid="KBasePublicNetwork",
ref_network=None,
out_id=None):
"""This method annotate GO terms and execute GO enrichment test
:param feature_set_id: FeatureSet workspace object id
:type feature_set_id: kbtypes.KBaseSearch.FeatureSet
:param p_value: p-value cutoff
:type p_value: kbtypes.Unicode
:param ref_wsid: Reference Network workspace id (optional, default to current workspace)
:type ref_wsid: kbtypes.Unicode
:param ref_network: Reference Network object name
:type ref_network:kbtypes.KBaseNetworks.Network
:param out_id: Output FeatureSet object identifier
:type out_id: kbtypes.KBaseSearch.FeatureSet
:return: New workspace object
:rtype: kbtypes.Unicode
:output_widget: GeneTableWidget
"""
meth.stages = 3
meth.advance("Prepare Enrichment Test")
oc = Ontology(url=URLS.ontology)
ws = Workspace2(token=meth.token, wsid=meth.workspace_id)
fs = ws.get(feature_set_id)
if not ref_wsid: ref_wsid = meth.workspace_id
ws2 = Workspace2(token=meth.token, wsid=ref_wsid)
net = ws2.get(ref_network)
# checking user input
if 'edges' not in net or 'nodes' not in net or 'elements' not in fs:
return "{}"
qid2cds = ids2cds(fs['elements'].keys())
# parse networks object
nc = Node(net['nodes'], net['edges'])
meth.advance("Execute Enrichment Test")
qcdss = set(qid2cds.values())
enr_dict = oc.association_test(list(qcdss), ref_wsid, ref_network, '',
'hypergeometric', 'none', p_value)
enr_list = sorted([(value, key) for (key, value) in enr_dict.items()])
nid2name = {}
for ne in net['nodes']:
nid2name[ne['entity_id']] = ne['name']
pwy_enr_smry = ""
header = ["Pathway ID", "Name", "p-value", "FeatureSet ID (# genes)"]
fields = []
objects = []
for i in range(len(enr_list)):
pwy_en = enr_list[i]
if float(pwy_en[0]) > float(p_value): continue
cgenes = set(nc.get_gene_list(pwy_en[1]))
cgenes = list(cgenes.intersection(qcdss))
cfs = genelist2fs(cgenes)
fields.append([
pwy_en[1], nid2name[pwy_en[1]],
"{:12.10f}".format(float(pwy_en[0])),
out_id + "_to_" + pwy_en[1] + "({})".format(len(cgenes))
])
objects.append({
'type': 'KBaseSearch.FeatureSet',
'data': cfs,
'name': out_id + "_to_" + pwy_en[1],
'meta': {
'original': feature_set_id,
'ref_wsid': ref_wsid,
'ref_net': ref_network,
'pwy_id': pwy_en[1]
}
})
if i < 3:
pwy_enr_smry += pwy_en[1] + "(" + "{:6.4f}".format(float(
pwy_en[0])) + ")" + nid2name[pwy_en[1]] + "\n"
data = {'table': [header] + fields}
meth.advance("Saving output to Workspace")
objects.append({
'type': 'KBaseSearch.FeatureSet',
'data': fs,
'name': out_id,
'meta': {
'original': feature_set_id,
'ref_wsid': ref_wsid,
'ref_net': ref_network,
'pwy_enr_summary': pwy_enr_smry
}
})
ws.save_objects({'workspace': meth.workspace_id, 'objects': objects})
meth.advance("Returning object")
return json.dumps(data)
def featureset_net_enr(meth, feature_set_id=None, p_value=None, ref_wsid="KBasePublicNetwork", ref_network=None, out_id=None):
"""This method annotate GO terms and execute GO enrichment test
:param feature_set_id: FeatureSet workspace object id
:type feature_set_id: kbtypes.KBaseSearch.FeatureSet
:param p_value: p-value cutoff
:type p_value: kbtypes.Unicode
:param ref_wsid: Reference Network workspace id (optional, default to current workspace)
:type ref_wsid: kbtypes.Unicode
:param ref_network: Reference Network object name
:type ref_network:kbtypes.KBaseNetworks.Network
:param out_id: Output FeatureSet object identifier
:type out_id: kbtypes.KBaseSearch.FeatureSet
:return: New workspace object
:rtype: kbtypes.Unicode
:output_widget: GeneTableWidget
"""
meth.stages = 3
meth.advance("Prepare Enrichment Test")
oc = Ontology(url=URLS.ontology)
ws = Workspace2(token=meth.token, wsid=meth.workspace_id)
fs = ws.get(feature_set_id)
if not ref_wsid : ref_wsid = meth.workspace_id
ws2 = Workspace2(token=meth.token, wsid=ref_wsid)
net = ws2.get(ref_network)
# checking user input
if 'edges' not in net or 'nodes' not in net or 'elements' not in fs: return "{}"
qid2cds = ids2cds(fs['elements'].keys())
# parse networks object
nc = Node(net['nodes'],net['edges']);
meth.advance("Execute Enrichment Test")
qcdss = set(qid2cds.values())
enr_dict = oc.association_test(list(qcdss), ref_wsid, ref_network, '', 'hypergeometric', 'none', p_value)
enr_list = sorted([(value,key) for (key,value) in enr_dict.items()])
nid2name = {}
for ne in net['nodes']:
nid2name[ne['entity_id']] = ne['name']
pwy_enr_smry = ""
header = ["Pathway ID", "Name", "p-value", "FeatureSet ID (# genes)"]
fields = []
objects = []
for i in range(len(enr_list)):
pwy_en = enr_list[i]
if float(pwy_en[0]) > float(p_value) : continue
cgenes = set(nc.get_gene_list(pwy_en[1]))
cgenes = list(cgenes.intersection(qcdss))
cfs = genelist2fs(cgenes)
fields.append([pwy_en[1], nid2name[pwy_en[1]], "{:12.10f}".format(float(pwy_en[0])), out_id + "_to_" + pwy_en[1] + "({})".format(len(cgenes))])
objects.append({'type' : 'KBaseSearch.FeatureSet', 'data' : cfs, 'name' : out_id + "_to_" + pwy_en[1], 'meta' : {'original' : feature_set_id, 'ref_wsid' : ref_wsid, 'ref_net' : ref_network, 'pwy_id' :pwy_en[1]}})
if i < 3 :
pwy_enr_smry += pwy_en[1]+"(" + "{:6.4f}".format(float(pwy_en[0])) + ")" + nid2name[pwy_en[1]] + "\n"
data = {'table': [header] + fields}
meth.advance("Saving output to Workspace")
objects.append({'type' : 'KBaseSearch.FeatureSet', 'data' : fs, 'name' : out_id, 'meta' : {'original' : feature_set_id, 'ref_wsid' : ref_wsid, 'ref_net' : ref_network, 'pwy_enr_summary' :pwy_enr_smry}})
ws.save_objects({'workspace' : meth.workspace_id, 'objects' :objects})
meth.advance("Returning object")
return json.dumps(data)
