# Create a Protein Disease graph from the DB adapter 'OlegDB'
from ProteinGraphML.DataAdapter import OlegDB
from ProteinGraphML.GraphTools import ProteinDiseaseAssociationGraph
## we construct a base map of protein to disease just by creating the ProteinDiseaseAs
dbAdapter = OlegDB()
proteinGraph = ProteinDiseaseAssociationGraph(dbAdapter)
## the 'ProteinDiseaseAssociationGraph' object has helper methods, but we can also access the networkx graph directly it is created with:
print('Total nodes: %d' % len(proteinGraph.graph.nodes))
## we will want to filter by the proteins we are interested in, this list comes from a DB adapter, but any set will do
proteins = dbAdapter.loadTotalProteinList().protein_id
filterByProteins = set(proteins)
# using .attach will add edges from a DB as defined by the adapter,
# with this method we can create a graph of data, which can itself be saved, prevents the
# need from, rebuilding as we work on different diseases, perform analysis
# We've also filter by proteins we care about, in this case it is our original list
proteinGraph.attach(dbAdapter.loadPPI(filterByProteins))
proteinGraph.attach(dbAdapter.loadKegg(filterByProteins))
proteinGraph.attach(dbAdapter.loadReactome(filterByProteins))
proteinGraph.attach(dbAdapter.loadInterpro(filterByProteins))
proteinGraph.attach(dbAdapter.loadGo(filterByProteins))
# networkx provides an api we can nodes from \n",
# here i exploit the unique features of each node to count them\n",
## Db is PonyORM db (https://docs.ponyorm.org/api_reference.html).
# Make TCRD as the default DB
dbad = OlegDB() if args.db == "olegdb" else TCRD()
pdg = ProteinDiseaseAssociationGraph(dbad)
## ProteinDiseaseAssociationGraph object has helper methods, but
## NetworkX methods also available.
## https://networkx.github.io/documentation/stable/reference/
logging.info('Total nodes: %d; edges: %d' %
(pdg.graph.order(), pdg.graph.size()))
## Filter by proteins of interest; this list comes from a DB adapter, but any set will do.
proteins = dbad.loadTotalProteinList().protein_id
proteinSet = set(proteins)
logging.info('Protein set: %d' % (len(proteinSet)))
# Using attach() add edges from DB.
# With this method create graph, which can be saved, avoiding
# need for rebuilding for different diseases, models and analyses.
# Also filter by proteins of interest, in this case it is our original list.
pdg.attach(dbad.loadPPI(proteinSet))
pdg.attach(dbad.loadKegg(proteinSet))
pdg.attach(dbad.loadReactome(proteinSet))
pdg.attach(dbad.loadGo(proteinSet))
try:
pdg.attach(dbad.loadInterpro(proteinSet))
except Exception as e: