Advances in computational approaches for prioritizing driver mutations and significantly mutated genes in cancer genomes.

ABSTRACT: Cancer is often driven by the accumulation of genetic alterations, including single nucleotide variants, small insertions or deletions, gene fusions, copy-number variations, and large chromosomal rearrangements. Recent advances in next-generation sequencing technologies have helped investigators generate massive amounts of cancer genomic data and catalog somatic mutations in both common and rare cancer types. So far, the somatic mutation landscapes and signatures of >10 major cancer types have been reported; however, pinpointing driver mutations and cancer genes from millions of available cancer somatic mutations remains a monumental challenge. To tackle this important task, many methods and computational tools have been developed during the past several years and, thus, a review of its ad

SUBMITTER: Cheng F 

PROVIDER: S-EPMC4945827 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature