Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits.

ABSTRACT:

Background

Dense SNP genotypes are often combined with complex trait phenotypes to map causal variants, study genetic architecture and provide genomic predictions for individuals with genotypes but no phenotype. A single method of analysis that jointly fits all genotypes in a Bayesian mixture model (BayesR) has been shown to competitively address all 3 purposes simultaneously. However, BayesR and other similar methods ignore prior biological knowledge and assume all genotypes are equally likely to affect the trait. While this assumption is reasonable for SNP array genotypes, it is less sensible if genotypes are whole-genome sequence variants which should include causal variants.

Results

We introduce a new method (BayesRC) based on BayesR that incorporates prior biological in

SUBMITTER: MacLeod IM 

PROVIDER: S-EPMC4769584 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature