HEFT: eQTL analysis of many thousands of expressed genes while simultaneously controlling for hidden factors.

ABSTRACT:

Motivation

Identification of expression Quantitative Trait Loci (eQTL), the genetic loci that contribute to heritable variation in gene expression, can be obstructed by factors that produce variation in expression profiles if these factors are unmeasured or hidden from direct analysis.

Methods

We have developed a method for Hidden Expression Factor analysis (HEFT) that identifies individual and pleiotropic effects of eQTL in the presence of hidden factors. The HEFT model is a combined multivariate regression and factor analysis, where the complete likelihood of the model is used to derive a ridge estimator for simultaneous factor learning and detection of eQTL. HEFT requires no pre-estimation of hidden factor effects; it provides P-values and is extremely fast, requiring jus

SUBMITTER: Gao C 

PROVIDER: S-EPMC3904522 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature