Network-Based Analysis of eQTL Data to Prioritize Driver Mutations.

ABSTRACT: In clonal systems, interpreting driver genes in terms of molecular networks helps understanding how these drivers elicit an adaptive phenotype. Obtaining such a network-based understanding depends on the correct identification of driver genes. In clonal systems, independent evolved lines can acquire a similar adaptive phenotype by affecting the same molecular pathways, a phenomenon referred to as parallelism at the molecular pathway level. This implies that successful driver identification depends on interpreting mutated genes in terms of molecular networks. Driver identification and obtaining a network-based understanding of the adaptive phenotype are thus confounded problems that ideally should be solved simultaneously. In this study, a network-based eQTL method is presented that solves

SUBMITTER: De Maeyer D 

PROVIDER: S-EPMC4825419 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature