Joint modelling of confounding factors and prominent genetic regulators provides increased accuracy in genetical genomics studies.

ABSTRACT: Expression quantitative trait loci (eQTL) studies are an integral tool to investigate the genetic component of gene expression variation. A major challenge in the analysis of such studies are hidden confounding factors, such as unobserved covariates or unknown subtle environmental perturbations. These factors can induce a pronounced artifactual correlation structure in the expression profiles, which may create spurious false associations or mask real genetic association signals. Here, we report PANAMA (Probabilistic ANAlysis of genoMic dAta), a novel probabilistic model to account for confounding factors within an eQTL analysis. In contrast to previous methods, PANAMA learns hidden factors jointly with the effect of prominent genetic regulators. As a result, this new model can more accurat

SUBMITTER: Fusi N 

PROVIDER: S-EPMC3252274 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature