An Evaluation of 'Deflation' to Improve Convergence Rates for Single-Step Genomic Evaluation with the Hybrid Model

Author(s)
Meyer, K
Swan, A A
Publication Date
2019-11
Abstract
Single step genomic evaluation fitting a 'hybrid' model which combines marker effects for individuals with genotypes with breeding values for non-genotyped animals can readily accommodate large numbers of genotyped animals. However, iterative solution of the pertaining mixed model equations via a preconditioned gradient scheme has been reported to be afflicted by much slower convergence rates than the standard breeding value model. 'Deflation' of the coefficient matrix has been proposed as a second preconditioning step and shown to dramatically reduce numbers of iterations and computing time required. We describe its application for a set of sheep data. Results indicate that assignment of marker effects to subdomains in moderately sized chunks together with a separate treatment of genetic group effects could reduce total computing times by about a third.
Citation
Proceedings of the Association for the Advancement of Animal Breeding and Genetics, v.23, p. 246-249
ISSN
1328-3227
Link
Language
en
Publisher
Association for the Advancement of Animal Breeding and Genetics (AAABG)
Title
An Evaluation of 'Deflation' to Improve Convergence Rates for Single-Step Genomic Evaluation with the Hybrid Model
Type of document
Conference Publication
Entity Type
Publication

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