Next-generation sequencing has allowed identification of millions of somatic mutations and epigenetic changes in cancer cells. A key challenge in interpreting cancer genomes and epigenomes is distinguishing which genetic and epigenetic changes are drivers of cancer development. Frequency-based and function-based approaches have been developed to identify candidate drivers; we discuss the advantages and drawbacks of these methods as well as their latest refinements. We focus particularly on identification of the types of drivers most likely to be missed, such as genes affected by copy number alterations, mutations in noncoding regions, dysregulation of microRNA, epigenetic changes, and mutations in chromatin modifiers.


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