'../data/UniprotKB/graph.json',
'../data/GO/graph.json',
'../data/PharmGKB/graph.json',
# '../data/PubMed/graph.json',
]
# Fusion
print('[INFO] Network fusion')
for graph in graphs:
print('[INFO] Add network', graph)
with io.open(graph, 'r', encoding='utf-8', newline='') as f:
g = json.loads(f.read())
network.load_from_dict(g)
# Mapping
print('[INFO] Add disease mappings')
all_disease_ids = set()
for node in network.get_nodes_by_label('Disease'):
all_disease_ids.update(node.ids)
for disease_id in all_disease_ids:
mapped_ids, mapped_names = mondo_mapper.map_from(disease_id)
if mapped_ids:
network.add_node(Disease(mapped_ids, mapped_names))
# Cleanup
print('[INFO] Prune network')
network.prune()
print('[INFO] Merge duplicate node names')
merge_duplicate_node_names(network)
print('[INFO] Merge duplicate edges')
network.merge_duplicate_edges()
# Export
print('[INFO] Export network')
directory_utils.create_clean_directory(config['output-path'])
def save_network(network: Network, config: Dict):
output_path = config['output-path']
# Save nodes
node_import_files = []
for label in network.node_labels():
file_name = 'nodes_%s.csv' % label.replace(';', '_')
nodes = set(network.get_nodes_by_label(label))
if len(nodes) > 0:
node_import_files.append(file_name)
with io.open(os.path.join(output_path, file_name),
'w',
encoding='utf-8',
newline='') as f:
writer = csv.writer(f, delimiter=',', quotechar='"')
all_attribute_keys = set()
for n in nodes:
all_attribute_keys.update(n.attributes.keys())
all_attribute_keys = sorted(all_attribute_keys)
writer.writerow([
'label_id:ID(Node-ID)', '_id:string', 'ids:string[]',
'names:string[]'
] + ['%s:string' % x for x in all_attribute_keys] + [':LABEL'])
for n in nodes:
row = [
n.label_id, n.id, ';'.join(n.ids), ';'.join(n.names)
]
for key in all_attribute_keys:
row.append(n.attributes[key] if key in
n.attributes else None)
row.append(n.label)
writer.writerow(row)
edge_metadata = {
'HAS_MOLECULAR_FUNCTION': [['source:string', 'pmid:string'],
['source',
'pmid']], # pmid int now not string
'BELONGS_TO_BIOLOGICAL_PROCESS': [['source:string', 'pmid:string'],
['source', 'pmid']],
'IN_CELLULAR_COMPONENT': [['source:string', 'pmid:string'],
['source', 'pmid']],
'INDICATES': [['source:string'], ['source']],
'REGULATES': [['source:string', 'pmid:string'], ['source', 'pmid']],
'TRANSCRIBES': [['source:string'], ['source']],
'CONTRAINDICATES': [['source:string'], ['source']],
'INDUCES': [['source:string'], ['source']],
'CODES': [['source:string', 'pmid:int'], ['source', 'pmid']],
'EQTL': [[
'source:string', 'pvalue:string', 'snp_chr:string',
'cis_trans:string'
], ['source', 'pvalue', 'snp_chr', 'cis_trans']],
'INTERACTS': [['source:string', 'description:string'],
['source', 'description']],
'TARGETS': [[
'source:string', 'known_action:boolean', 'actions:string[]',
'simplified_action:string'
],
[
'source', lambda attr:
('true' if attr['known_action'] else 'false')
if 'known_action' in attr else None,
lambda attr: ';'.join(attr['actions']),
'simplified_action'
]],
'ASSOCIATES_WITH':
[['source:string', 'num_pmids:int', 'num_snps:int', 'score:string'],
['source', 'num_pmids', 'num_snps', 'score']],
'HAS_ADR': [['source:string'], ['source']],
'ASSOCIATED_WITH_ADR': [['source:string'], ['source']]
}
# Save relationships
for x in edge_metadata:
with io.open(os.path.join(output_path, 'rel_%s.csv' % x),
'w',
encoding='utf-8',
newline='') as f:
writer = csv.writer(f, delimiter=',', quotechar='"')
writer.writerow([':START_ID(Node-ID)'] + edge_metadata[x][0] +
[':END_ID(Node-ID)', ':TYPE'])
for e in network.get_edges_by_label(x):
values = []
for l in edge_metadata[x][1]:
if isinstance(l, type(lambda: 0)):
values.append(l(e.attributes))
else:
values.append(e.attributes[l] if l in
e.attributes else None)
source_id = network.get_node_by_id(
e.source_node_id, e.source_node_label).label_id
target_id = network.get_node_by_id(
e.target_node_id, e.target_node_label).label_id
writer.writerow([source_id] + values + [target_id, e.label])
with io.open(os.path.join(output_path, 'create_indices.cypher'),
'w',
encoding='utf-8',
newline='') as f:
unique_labels = set()
for node_label in network.node_labels():
unique_labels.update(set(node_label.split(';')))
for node_label in unique_labels:
f.write('create constraint on (p:%s) assert p._id is unique;\n' %
node_label)
with io.open(os.path.join(output_path, 'import_admin.bat'),
'w',
encoding='utf-8',
newline='') as f:
f.write('@echo off\n')
f.write('net stop neo4j\n')
f.write('rmdir /s "%s"\n' %
os.path.join(config['Neo4j']['database-path'],
config['Neo4j']['database-name']))
f.write('CALL ' +
os.path.join(config['Neo4j']['bin-path'], 'neo4j-admin'))
f.write(' import ' +
'--database %s ' % config['Neo4j']['database-name'] +
' '.join(['--nodes %s' % x
for x in node_import_files]) + ' ' + ' '.join([
'--relationships rel_%s.csv' % x
for x in network.edge_labels()
]) + ' > import.log\n')
f.write('net start neo4j\n')
f.write(os.path.join(config['Neo4j']['bin-path'], 'cypher-shell'))
f.write(
' -u %s -p %s --non-interactive < create_indices.cypher 1>> import.log 2>&1\n'
% (config['Neo4j']['user'], config['Neo4j']['password']))
with io.open(os.path.join(output_path, 'import_admin.sh'),
'w',
encoding='utf-8',
newline='') as f:
f.write(os.path.join(config['Neo4j']['bin-path'], 'neo4j-admin'))
f.write(' import ' +
'--database %s ' % config['Neo4j']['database-name'] +
' '.join(['--nodes %s' % x
for x in node_import_files]) + ' ' + ' '.join([
'--relationships rel_%s.csv' % x
for x in network.edge_labels()
]) + ' > import.log\n')
f.write(
'<li><a href="#loss-distinction-section">Possible loss of distinction</a></li>\n'
)
f.write(
'<li><a href="#single-id-nodes">Nodes with single IDs</a></li>\n')
f.write('</ul>\n')
f.write(
'<h1><a name="indi-contra-section">Drugs indicating and contraindicating same disease:</a></h1>\n'
)
f.write(
'<table border="1">\n<thead>\n<tr><th>Drug</th><th>Indications</th><th>Contraindications</th></tr>\n</thead>\n'
)
f.write('<tbody>\n')
drug_count = 0
drug_check_failed_count = 0
for drug in network.get_nodes_by_label('Drug'):
drug_count += 1
indications = {
x.target_node_id
for x in network.get_node_edges_by_label(drug, 'INDICATES')
}
contraindications = {
x.target_node_id
for x in network.get_node_edges_by_label(
drug, 'CONTRAINDICATES')
}
if not indications.isdisjoint(contraindications):
drug_check_failed_count += 1
for intersection in indications.intersection(
contraindications):
