Distinguishing between driver and passenger mutations in individual cancer genomes by network enrichment analysis.

ABSTRACT:

Background

In somatic cancer genomes, delineating genuine driver mutations against a background of multiple passenger events is a challenging task. The difficulty of determining function from sequence data and the low frequency of mutations are increasingly hindering the search for novel, less common cancer drivers. The accumulation of extensive amounts of data on somatic point and copy number alterations necessitates the development of systematic methods for driver mutation analysis.

Results

We introduce a framework for detecting driver mutations via functional network analysis, which is applied to individual genomes and does not require pooling multiple samples. It probabilistically evaluates 1) functional network links between different mutations in the same genome and 2)

SUBMITTER: Merid SK 

PROVIDER: S-EPMC4262241 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature