Joint prediction of multiple quantitative traits using a Bayesian multivariate antedependence model.

ABSTRACT: Predicting organismal phenotypes from genotype data is important for preventive and personalized medicine as well as plant and animal breeding. Although genome-wide association studies (GWAS) for complex traits have discovered a large number of trait- and disease-associated variants, phenotype prediction based on associated variants is usually in low accuracy even for a high-heritability trait because these variants can typically account for a limited fraction of total genetic variance. In comparison with GWAS, the whole-genome prediction (WGP) methods can increase prediction accuracy by making use of a huge number of variants simultaneously. Among various statistical methods for WGP, multiple-trait model and antedependence model show their respective advantages. To take advantage of both

SUBMITTER: Jiang J 

PROVIDER: S-EPMC4815501 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature