A singular value decomposition Bayesian multiple-trait and multiple-environment genomic model.

ABSTRACT: Today, breeders perform genomic-assisted breeding to improve more than one trait. However, frequently there are several traits under study at one time, and the implementation of current genomic multiple-trait and multiple-environment models is challenging. Consequently, we propose a four-stage analysis for multiple-trait data in this paper. In the first stage, we perform singular value decomposition (SVD) on the resulting matrix of trait responses; in the second stage, we perform multiple trait analysis on transformed responses. In stages three and four, we collect and transform the traits back to their original state and obtain the parameter estimates and the predictions on these scale variables prior to transformation. The results of the proposed method are compared, in terms of paramete

SUBMITTER: Montesinos-Lopez OA 

PROVIDER: S-EPMC6460759 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature