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.
CITATION STYLE
Mularoni, L., Sabarinathan, R., Deu-Pons, J., Gonzalez-Perez, A., & López-Bigas, N. (2016). OncodriveFML: A general framework to identify coding and non-coding regions with cancer driver mutations. Genome Biology, 17(1). https://doi.org/10.1186/s13059-016-0994-0
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