PLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies.

ABSTRACT: Multilocus genome-wide association studies (GWAS) have become the state-of-the-art procedure to identify quantitative trait nucleotides (QTNs) associated with complex traits. However, implementation of multilocus model in GWAS is still difficult. In this study, we integrated least angle regression with empirical Bayes to perform multilocus GWAS under polygenic background control. We used an algorithm of model transformation that whitened the covariance matrix of the polygenic matrix K and environmental noise. Markers on one chromosome were included simultaneously in a multilocus model and least angle regression was used to select the most potentially associated single-nucleotide polymorphisms (SNPs), whereas the markers on the other chromosomes were used to calculate kinship matrix as poly

SUBMITTER: Zhang J 

PROVIDER: S-EPMC5436030 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature