OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations. Issue 1 (December 2016) - Mularoni, Loris; Sabarinathan, Radhakrishnan; Deu-Pons, Jordi; Gonzalez-Perez, Abel; López-Bigas, Núria
Abstract Distinguishing the driver mutations from somatic mutations in a tumor genome is one of the major challenges of cancer research. This challenge is more acute and far from solved for non-coding mutations. Here we present OncodriveFML, a method designed to analyze the pattern of somatic mutations across tumors in both coding and non-coding genomic regions to identify signals of positive selection, and therefore, their involvement in tumorigenesis. We describe the method and illustrate its usefulness to identify protein-coding genes, promoters, untranslated regions, intronic splice regions, and lncRNAs-containing driver mutations in several malignancies.