def genelist2fs(gl):
qid2cds = ids2cds(gl)
fs = {
"description": "Feature set generated by " + ",".join(gl),
"elements": {}
}
cdmie = CDMI_EntityAPI(URLS.cdmi)
cdmic = CDMI_API(URLS.cdmi)
cds_ids = qid2cds.values()
cds2l = cds2locus(cds_ids)
lfunc = cdmic.fids_to_functions(cds2l.values())
fm = cdmie.get_entity_Feature(
cds_ids,
['feature_type', 'source_id', 'sequence_length', 'function', 'alias'])
for i in cds_ids:
if i in fm:
if not fm[i]['function'] and cds2l[i] in lfunc:
fm[i]['function'] = lfunc[cds2l[i]]
fs['elements'][i] = {
"data": {
'type': fm[i]['feature_type'],
'id': i,
'dna_sequence_length': int(fm[i]['sequence_length']),
'function': fm[i]['function'],
'aliases': fm[i]['alias']
}
}
return fs
def genelist2fs(gl):
qid2cds = ids2cds(gl)
fs = {"description" : "Feature set generated by " + ",".join(gl),
"elements" : {}
}
cdmie = CDMI_EntityAPI(URLS.cdmi)
cdmic = CDMI_API(URLS.cdmi)
cds_ids = qid2cds.values()
cds2l = cds2locus(cds_ids);
lfunc = cdmic.fids_to_functions(cds2l.values())
fm = cdmie.get_entity_Feature(cds_ids,['feature_type', 'source_id', 'sequence_length', 'function', 'alias'])
for i in cds_ids:
if i in fm:
if not fm[i]['function'] and cds2l[i] in lfunc:
fm[i]['function'] = lfunc[cds2l[i]]
fs['elements'][i] = {"data" : { 'type' : fm[i]['feature_type'], 'id' : i, 'dna_sequence_length' : int(fm[i]['sequence_length']), 'function' : fm[i]['function'], 'aliases' : fm[i]['alias']}}
return fs
def go_anno_net(meth, net_obj_id=None):
"""Add Gene Ontology annotation to network gene nodes
:param net_obj_id: Network object id
:type net_obj_id: kbtypes.KBaseNetworks.Network
:return: Workspace id
:rtype: kbtypes.Unicode
:output_widget: ValueListWidget
"""
meth.stages = 5
meth.advance("Prepare annotation service")
#gc = GWAS(URLS.gwas, token=meth.token)
# load from current or other workspace
wsid = meth.workspace_id
# save to current workspace
ws_save_id = meth.workspace_id
meth.advance("Load network object")
wsd = Workspace2(token=meth.token, wsid=wsid)
oc = Ontology(url=URLS.ontology)
net_object = wsd.get(net_obj_id)
nc = Node(net_object['nodes'], net_object['edges'])
idc = IDServerAPI(URLS.ids)
cdmic = CDMI_API(URLS.cdmi)
cdmie = CDMI_EntityAPI(URLS.cdmi)
#idm = IdMap(URLS.idmap)
gids = [
i for i in sorted(nc.ugids.keys()) if 'CDS' in i or 'locus' in i or (
not 'clst' in i and not i.startswith('cluster') and 'ps.' not in i)
]
meth.advance("Get relationships from central data model")
#eids = idc.kbase_ids_to_external_ids(gids)
eids = kb_id2ext_id(idc, gids, 100)
gids2cds = ids2cds(gids)
cgids = gids2cds.values()
cds2l = cds2locus(cgids)
#mrnas_l = cdmie.get_relationship_Encompasses(gids, [], ['to_link'], [])
#mrnas = dict((i[1]['from_link'], i[1]['to_link']) for i in mrnas_l)
#locus_l = cdmie.get_relationship_Encompasses(mrnas.values(), [], ['to_link'], [])
#locus = dict((i[1]['from_link'], i[1]['to_link']) for i in locus_l)
#lgids = [locus[mrnas[i]] for i in gids if i in mrnas.keys()] # ignore original locus ids in gids
lgids = cds2l.values()
meth.advance("Annotate ({:d} nodes, {:d} edges)".format(
len(net_object['nodes']), len(net_object['edges'])))
#ots = oc.get_goidlist(lgids, ['biological_process'], ['IEA'])
ots = oc.get_goidlist(cgids, [], [])
oan = () #oc.get_go_annotation(lgids)
funcs = cdmic.fids_to_functions(lgids)
funcs_org = cdmic.fids_to_functions(cgids)
annotate_nodes(net_object,
ots=ots,
oan=oan,
funcs=funcs,
funcs_org=funcs_org,
eids=eids,
gids2cds=gids2cds,
cds2l=cds2l)
meth.advance("Save annotated object to workspace {}".format(ws_save_id))
obj = {
'type': 'KBaseNetworks.Network',
'data': net_object,
'name': net_obj_id + ".ano",
'meta': {
'original': net_obj_id
}
}
wsd.save_objects({'workspace': ws_save_id, 'objects': [obj]})
return _workspace_output(net_obj_id + ".ano")
def featureset_go_anal(meth,
feature_set_id=None,
p_value=0.05,
ec='IEA',
domain='biological_process',
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 ec: Evidence code list (comma separated, IEA,ISS,IDA,IEP,IPI,RCA ..)
:type ec:kbtypes.Unicode
:param domain: Domain list (comma separated, biological_process,molecular_function,cellular_component)
:type domain: kbtypes.Unicode
: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 = 4
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)
qid2cds = ids2cds(fs['elements'].keys())
cds2l = cds2locus(qid2cds.values())
cdmic = CDMI_API(URLS.cdmi)
lfunc = cdmic.fids_to_functions(cds2l.values())
meth.advance("Annotate GO Term")
ec = ec.replace(" ", "")
domain = domain.replace(" ", "")
ec_list = [i for i in ec.split(',')]
domain_list = [i for i in domain.split(',')]
ots = oc.get_goidlist(list(set(qid2cds.values())), domain_list, ec_list)
go_key = lambda go, i, ext: "go.{}.{:d}.{}".format(go, i, ext)
go2cds = {}
for gid in fs['elements']:
lid = qid2cds[gid]
if 'data' in fs['elements'][gid]:
if not fs['elements'][gid]['data']['function']:
fs['elements'][gid]['data']['function'] = lfunc[cds2l[lid]]
if 'metadata' not in fs['elements'][gid]:
fs['elements'][gid]['metadata'] = {}
if lid in ots:
go_enr_list = []
for lcnt, go in enumerate(ots[lid].keys()):
if go not in go2cds: go2cds[go] = set()
go2cds[go].add(lid)
for i, goen in enumerate(ots[lid][go]):
for ext in "domain", "ec", "desc":
fs['elements'][gid]['metadata'][go_key(
go, i, ext)] = goen[ext]
fs['elements'][gid]['metadata'][go_key(
go, i, ext)] = goen[ext]
meth.advance("Execute Enrichment Test")
enr_list = oc.get_go_enrichment(list(set(qid2cds.values())), domain_list,
ec_list, 'hypergeometric', 'GO')
enr_list = sorted(enr_list, key=itemgetter('pvalue'), reverse=False)
header = [
"GO ID", "Description", "Domain", "p-value", "FeatureSet ID (# genes)"
]
fields = []
objects = []
go_enr_smry = ""
for i in range(len(enr_list)):
goen = enr_list[i]
if goen['pvalue'] > float(p_value): continue
cfs = genelist2fs(list(go2cds[goen['goID']]))
goid = goen['goID'].replace(":", "")
fields.append([
goen['goID'], goen['goDesc'][0], goen['goDesc'][1],
"{:12.10f}".format(goen['pvalue']),
"{}_to_{} ({})".format(out_id, goid, len(go2cds[goen['goID']]))
])
objects.append({
'type': 'KBaseSearch.FeatureSet',
'data': cfs,
'name': out_id + "_to_" + goid,
'meta': {
'original': feature_set_id,
'domain': domain,
'ec': ec,
'GO_ID': goen['goID']
}
})
if i < 3:
go_enr_smry += goen['goID'] + "(" + "{:6.4f}".format(
goen['pvalue']) + ")" + goen['goDesc'][0] + "\n"
go_enr_smry
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,
'enr_summary': go_enr_smry
}
})
ws.save_objects({'workspace': meth.workspace_id, 'objects': objects})
return json.dumps(data)
def go_anno_net(meth, net_obj_id=None):
"""Add Gene Ontology annotation to network gene nodes
:param net_obj_id: Network object id
:type net_obj_id: kbtypes.KBaseNetworks.Network
:return: Workspace id
:rtype: kbtypes.Unicode
:output_widget: ValueListWidget
"""
meth.stages = 5
meth.advance("Prepare annotation service")
#gc = GWAS(URLS.gwas, token=meth.token)
# load from current or other workspace
wsid = meth.workspace_id
# save to current workspace
ws_save_id = meth.workspace_id
meth.advance("Load network object")
wsd = Workspace2(token=meth.token, wsid=wsid)
oc = Ontology(url=URLS.ontology)
net_object = wsd.get(net_obj_id)
nc = Node(net_object['nodes'], net_object['edges'])
idc = IDServerAPI(URLS.ids)
cdmic = CDMI_API(URLS.cdmi)
cdmie = CDMI_EntityAPI(URLS.cdmi)
#idm = IdMap(URLS.idmap)
gids = [i for i in sorted(nc.ugids.keys())
if 'CDS' in i or 'locus' in i or (not 'clst' in i and not i.startswith('cluster') and 'ps.' not in i )]
meth.advance("Get relationships from central data model")
#eids = idc.kbase_ids_to_external_ids(gids)
eids = kb_id2ext_id(idc, gids, 100)
gids2cds = ids2cds(gids)
cgids = gids2cds.values()
cds2l = cds2locus(cgids)
#mrnas_l = cdmie.get_relationship_Encompasses(gids, [], ['to_link'], [])
#mrnas = dict((i[1]['from_link'], i[1]['to_link']) for i in mrnas_l)
#locus_l = cdmie.get_relationship_Encompasses(mrnas.values(), [], ['to_link'], [])
#locus = dict((i[1]['from_link'], i[1]['to_link']) for i in locus_l)
#lgids = [locus[mrnas[i]] for i in gids if i in mrnas.keys()] # ignore original locus ids in gids
lgids = cds2l.values()
meth.advance("Annotate ({:d} nodes, {:d} edges)".format(
len(net_object['nodes']), len(net_object['edges'])))
#ots = oc.get_goidlist(lgids, ['biological_process'], ['IEA'])
ots = oc.get_goidlist(cgids, [], [])
oan = () #oc.get_go_annotation(lgids)
funcs = cdmic.fids_to_functions(lgids)
funcs_org = cdmic.fids_to_functions(cgids)
annotate_nodes(net_object, ots=ots, oan=oan, funcs=funcs, funcs_org=funcs_org, eids=eids,
gids2cds=gids2cds, cds2l=cds2l)
meth.advance("Save annotated object to workspace {}".format(ws_save_id))
obj = {
'type': 'KBaseNetworks.Network',
'data': net_object,
'name': net_obj_id + ".ano",
'meta': {
'original': net_obj_id
}
}
wsd.save_objects({'workspace': ws_save_id, 'objects': [obj]})
return _workspace_output(net_obj_id + ".ano")
def featureset_go_anal(meth, feature_set_id=None, p_value=0.05, ec='IEA', domain='biological_process', 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 ec: Evidence code list (comma separated, IEA,ISS,IDA,IEP,IPI,RCA ..)
:type ec:kbtypes.Unicode
:param domain: Domain list (comma separated, biological_process,molecular_function,cellular_component)
:type domain: kbtypes.Unicode
: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 = 4
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)
qid2cds = ids2cds(fs['elements'].keys())
cds2l = cds2locus(qid2cds.values())
cdmic = CDMI_API(URLS.cdmi)
lfunc = cdmic.fids_to_functions(cds2l.values())
meth.advance("Annotate GO Term")
ec = ec.replace(" ","")
domain = domain.replace(" ","")
ec_list = [ i for i in ec.split(',')]
domain_list = [ i for i in domain.split(',')]
ots = oc.get_goidlist(list(set(qid2cds.values())), domain_list, ec_list)
go_key = lambda go, i, ext: "go.{}.{:d}.{}".format(go, i, ext)
go2cds = {}
for gid in fs['elements']:
lid = qid2cds[gid]
if 'data' in fs['elements'][gid]:
if not fs['elements'][gid]['data']['function']: fs['elements'][gid]['data']['function'] = lfunc[cds2l[lid]]
if 'metadata' not in fs['elements'][gid]: fs['elements'][gid]['metadata'] = {}
if lid in ots:
go_enr_list = []
for lcnt, go in enumerate(ots[lid].keys()):
if go not in go2cds: go2cds[go] = set()
go2cds[go].add(lid)
for i, goen in enumerate(ots[lid][go]):
for ext in "domain", "ec", "desc":
fs['elements'][gid]['metadata'][go_key(go, i, ext)] = goen[ext]
fs['elements'][gid]['metadata'][go_key(go, i, ext)] = goen[ext]
meth.advance("Execute Enrichment Test")
enr_list = oc.get_go_enrichment(list(set(qid2cds.values())), domain_list, ec_list, 'hypergeometric', 'GO')
enr_list = sorted(enr_list, key=itemgetter('pvalue'), reverse=False)
header = ["GO ID", "Description", "Domain", "p-value", "FeatureSet ID (# genes)"]
fields = []
objects = []
go_enr_smry = ""
for i in range(len(enr_list)):
goen = enr_list[i]
if goen['pvalue'] > float(p_value) : continue
cfs = genelist2fs(list(go2cds[goen['goID']]))
goid = goen['goID'].replace(":","")
fields.append([goen['goID'], goen['goDesc'][0], goen['goDesc'][1], "{:12.10f}".format(goen['pvalue']), "{}_to_{} ({})".format(out_id, goid,len(go2cds[goen['goID']])) ])
objects.append({'type' : 'KBaseSearch.FeatureSet', 'data' : cfs, 'name' : out_id + "_to_" + goid, 'meta' : {'original' : feature_set_id, 'domain' : domain, 'ec' : ec, 'GO_ID' :goen['goID']}})
if i < 3 :
go_enr_smry += goen['goID']+"(" + "{:6.4f}".format(goen['pvalue']) + ")" + goen['goDesc'][0] + "\n"
go_enr_smry
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, 'enr_summary' : go_enr_smry}})
ws.save_objects({'workspace' : meth.workspace_id, 'objects' :objects})
return json.dumps(data)
