Mularoni, LorisSabarinathan, RadhakrishnanDéu Pons, JordiGonzález-Pérez, AbelLópez Bigas, Núria2016-11-282016-11-282016Mularoni L, Sabarinathan R, Déu Pons J, González-Pérez A, López Bigas N. OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations. Genome Biology. 2016;17:128. DOI: 10.1186/s13059-016-0994-01474-760Xhttp://hdl.handle.net/10230/27626Distinguishing 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.application/pdfeng© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.info:eu-repo/semantics/articlehttp://dx.doi.org/10.1186/s13059-016-0994-0Cancer driversNon-coding regionsLocal functional mutations biasNon-coding driversinfo:eu-repo/semantics/openAccess