def generateNetworkVisualizationFiles(drugsfile, targetsfile, proteinnodesfile):
fingerprints = util.readDrugData(drugsfile)
[targetSets, ligandSets] = util.readTargetData(targetsfile, fingerprints.keys())
# Unsorted protein nodes data
proteinNodes = np.loadtxt(proteinnodesfile, dtype='string', delimiter=',', skiprows=1)
# Protein nodes data, sorted alphabetically by protein name
sortedProteinNodes = proteinNodes[proteinNodes[:,0].argsort()]
# Initialize data structures
networkData=[]; nameData=[]; indicationData=[]; networkNodes=set()
# Iterate over each node pair to determine if their bootstrap p-value merits an edge connection
for i in range(len(sortedProteinNodes)):
for j in range(i+1, len(sortedProteinNodes)):
proteinA = sortedProteinNodes[i,0]
proteinB = sortedProteinNodes[j,0]
bootstrapPVal = util.calculateBootstrapPValue(100, 214, fingerprints, ligandSets, proteinA, proteinB)
if bootstrapPVal <= 0.05:
networkData.append([proteinA, proteinB]) # Create edge between connected nodes
networkNodes.update([proteinA, proteinB]) # Update set of nodes in network
# Annotate each node with its name and indication
for protein in proteinNodes:
if protein[0] in networkNodes:
nameData.append([protein[0],protein[1]])
indicationData.append([protein[0],protein[2]])
# Output files
np.savetxt('network.sif', np.array(networkData), fmt='%s edge %s')
np.savetxt('name.nodeAttr', np.array(nameData), fmt='%s = %s', header="name", comments='')
np.savetxt('indication.nodeAttr', np.array(indicationData), fmt='%s = %s', header="indication", comments='')
def initParams():
parser = argparse.ArgumentParser()
parser.add_argument('-n', metavar='n', type=int, default='100')
parser.add_argument('-r', metavar='r', type=int, default='214')
parser.add_argument('drugs', type=str)
parser.add_argument('targets', type=str)
parser.add_argument('proteinA', type=str)
parser.add_argument('proteinB', type=str)
args = parser.parse_args()
fingerprints = util.readDrugData(args.drugs)
[targetSets, ligandSets] = util.readTargetData(args.targets, fingerprints.keys())
# Return a dictionary with all parameters
return {'n':args.n,'r':args.r,
'fingerprints':fingerprints, 'ligandSets':ligandSets,
'proteinA':args.proteinA, 'proteinB':args.proteinB}
def initParams():
parser = argparse.ArgumentParser()
parser.add_argument('-n', metavar='n', type=int, default='100')
parser.add_argument('-r', metavar='r', type=int, default='214')
parser.add_argument('drugs', type=str)
parser.add_argument('targets', type=str)
parser.add_argument('proteinA', type=str)
parser.add_argument('proteinB', type=str)
args = parser.parse_args()
fingerprints = util.readDrugData(args.drugs)
[targetSets, ligandSets] = util.readTargetData(args.targets,
fingerprints.keys())
# Return a dictionary with all parameters
return {
'n': args.n,
'r': args.r,
'fingerprints': fingerprints,
'ligandSets': ligandSets,
'proteinA': args.proteinA,
'proteinB': args.proteinB
}
def tanimotoScoresForAllDrugPairs(drugsfile, targetsfile, outputfile):
fingerprints = util.readDrugData(drugsfile)
[targetSets, ligandSets] = util.readTargetData(targetsfile, fingerprints.keys())
util.computeAllTanimotoScores(fingerprints, targetSets, outputfile)
def tanimotoScoresForAllDrugPairs(drugsfile, targetsfile, outputfile):
fingerprints = util.readDrugData(drugsfile)
[targetSets, ligandSets] = util.readTargetData(targetsfile,
fingerprints.keys())
util.computeAllTanimotoScores(fingerprints, targetSets, outputfile)
