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iCAGES: integrated CAncer GEnome Score for comprehensively prioritizing driver genes in personal cancer genomes

1 Dec 2016

Abstract excerpt

Cancer results from the acquisition of somatic driver mutations. Several computational tools can predict driver genes from population-scale genomic data, but tools for analyzing personal cancer genomes are underdeveloped. Here we developed iCAGES, a novel statistical framework that infers driver variants by integrating contributions from coding, non-coding, and structural variants, identifies driver genes by...

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PMID: 28007024
DOI: 10.1186/s13073-016-0390-0

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