DriverNet: Drivernet: uncovering somatic driver mutations modulating transcriptional networks in cancer

DriverNet is a package to predict functional important driver genes in cancer by integrating genome data (mutation and copy number variation data) and transcriptome data (gene expression data). The different kinds of data are combined by an influence graph, which is a gene-gene interaction network deduced from pathway data. A greedy algorithm is used to find the possible driver genes, which may mutated in a larger number of patients and these mutations will push the gene expression values of the connected genes to some extreme values.

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AuthorAli Bashashati, Reza Haffari, Jiarui Ding, Gavin Ha, Kenneth Liu, Jamie Rosner and Sohrab Shah
Bioconductor views Network
Date of publicationNone
MaintainerJiarui Ding <>

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actualEvents Man page
actualEvents,DriverNetResult-method Man page
computeDrivers Man page
computeRandomizedResult Man page
DriverNet Man page
DriverNet-package Man page
DriverNetResult-class Man page
drivers Man page
drivers,DriverNetResult-method Man page
getPatientOutlierMatrix Man page
preprocessMatrices Man page
resultSummary Man page
sampleDriversList Man page
sampleGeneNames Man page
sampleInfluenceGraph Man page
samplePatientExpressionMatrix Man page
samplePatientMutationMatrix Man page
samplePatientOutlierMatrix Man page
sampleRandomDriversResult Man page
totalEvents Man page
totalEvents,DriverNetResult-method Man page

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