Learning gene networks under SNP perturbations using eQTL datasets.

ABSTRACT: The standard approach for identifying gene networks is based on experimental perturbations of gene regulatory systems such as gene knock-out experiments, followed by a genome-wide profiling of differential gene expressions. However, this approach is significantly limited in that it is not possible to perturb more than one or two genes simultaneously to discover complex gene interactions or to distinguish between direct and indirect downstream regulations of the differentially-expressed genes. As an alternative, genetical genomics study has been proposed to treat naturally-occurring genetic variants as potential perturbants of gene regulatory system and to recover gene networks via analysis of population gene-expression and genotype data. Despite many advantages of genetical genomics data a

SUBMITTER: Zhang L 

PROVIDER: S-EPMC3937098 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature