A Bayesian Genomic Multi-output Regressor Stacking Model for Predicting Multi-trait Multi-environment Plant Breeding Data

A Bayesian Genomic Multi-output Regressor Stacking Model for Predicting Multi-trait Multi-environment Plant Breeding Data

In this paper we propose a Bayesian multi-output regressor stacking (BMORS) model that is a generalization of the multi-trait regressor stacking method. The proposed BMORS model consists of two stages: in the first stage, a univariate genomic best linear unbiased prediction (GBLUP including genotype...

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Bibliographic Details
Main Authors: Osval A. Montesinos-López, Abelardo Montesinos-López, José Crossa, Jaime Cuevas, José C. Montesinos-López, Zitlalli Salas Gutiérrez, Morten Lillemo, Juliana Philomin, Ravi Singh
Format: Article
Language:English
Published: Oxford University Press 2019-10-01
Series:G3: Genes, Genomes, Genetics
Subjects:
Bayesian multi-output regressor stacking
multi-trait
multi-environment
GBLUP
genomic selection
breeding programs
regressor stacking
Genomic Prediction
GenPred
Shared Data Resources
Online Access:http://g3journal.org/lookup/doi/10.1534/g3.119.400336

Internet

http://g3journal.org/lookup/doi/10.1534/g3.119.400336

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