How to prioritize cancer somatic mutations?

Projects that sequence the genomes of a cohort of tumor samples are faced with the challenge of deciding which somatic mutations are relevant to tumor development (drivers). The exome of an individual tumor sample normally contains a few dozens of somatic mutations, most of which are thought to be passenger, i.e., they do not contribute to the tumor phenotype. Very often, cancer resequencing projects use known tools that assess the functional impact of individual mutations (eg. SIFT, PolyPhen2, Mutation Assessor) or use their recurrence across tumor samples to rank somatic variants. They also resort to accumulated knowledge by focusing on mutations that appear in known cancer genes. There are only few bioinformatics tools available to rank somatic mutations according to their likelihood of promoting tumorigenesis. Amongst them are CanPredict and CHASM. (Here is a comprehensive review.)

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