Usage

First open R, in Linux and Mac, just type R in shell. In R, type the following commands:

library(DriverNet)

data(samplePatientMutationMatrix)
data(samplePatientOutlierMatrix)
data(sampleInfluenceGraph)
data(sampleGeneNames)

# The main function to compute drivers
driversList = computeDrivers(samplePatientMutationMatrix, samplePatientOutlierMatrix,
sampleInfluenceGraph, outputFolder=NULL, printToConsole=FALSE)

drivers(driversList)[1:10]

# random permute the gene labels to compute p-values
randomDriversResult = computeRandomizedResult(patMutMatrix=samplePatientMutationMatrix,
patOutMatrix=samplePatientOutlierMatrix, influenceGraph=sampleInfluenceGraph,
geneNameList= sampleGeneNames, outputFolder=NULL, printToConsole=FALSE,
numberOfRandomTests=20, weight=FALSE, purturbGraph=FALSE, purturbData=TRUE)

# Summarize the results
res = resultSummary(driversList, randomDriversResult, samplePatientMutationMatrix,
sampleInfluenceGraph, outputFolder=NULL, printToConsole=FALSE)

Reproduce the paper results

First download the data file paperData.tar.gz and decompress it to the desired folder.
Open R, and load the influence graph

load("influenceGraph.rda") 
Then load one of the data file, e.g.,
load("GBM_data.rda")

and run

driversList = computeDrivers(patMutMatrix, patOutMatrix,
influenceGraph, outputFolder=NULL, printToConsole=FALSE) 

will give you the rank list of genes.