driveR: A Novel Method for Prioritizing Cancer Driver Genes Using Somatic Genomics Data

Abstract Cancer develops due to “driver” alterations. Numerous approaches exist for predicting cancer drivers from cohort-scale genomic data. However, methods for personalized analysis of driver genes are underdeveloped. In this study, we developed a novel personalized/batch analysis approach for driver gene prioritization utilizing somatic genomic data, called driveR. Combining genomic information and prior biological knowledge, driveR accurately prioritizes cancer driver genes via a multi-task learning model. Testing on 28 different datasets, this study demonstrates that driveR performs adequately, outperforms existing approaches, and is an accurate and easy-to-utilize approach for prioritizing driver genes in cancer genomes. driveR is available on CRAN: https://cran.r-project.org/package=driveR .