Genomic Prediction Accounting for Residual Heteroskedasticity

Genomic Prediction Accounting for Residual Heteroskedasticity

Whole-genome prediction (WGP) models that use single-nucleotide polymorphism marker information to predict genetic merit of animals and plants typically assume homogeneous residual variance. However, variability is often heterogeneous across agricultural production systems and may subsequently bias...

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Bibliographic Details
Main Authors:	Zhining Ou, Robert J. Tempelman, Juan P. Steibel, Catherine W. Ernst, Ronald O. Bates, Nora M. Bello
Format:	Article
Language:	English
Published:	Oxford University Press 2016-01-01
Series:	G3: Genes, Genomes, Genetics
Subjects:	whole-genome prediction heteroskedastic errors genomic breeding values hierarchical Bayesian model genPred shared data resource
Online Access:	http://g3journal.org/lookup/doi/10.1534/g3.115.022897

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