Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/18916
Title: Technical note: Genetic principal component models for multitrait single-step genomic evaluation
Contributor(s): Meyer, Karin  (author); Swan, Andrew  (author); Tier, Bruce  (author)
Publication Date: 2015
DOI: 10.2527/jas.2015-9333
Handle Link: https://hdl.handle.net/1959.11/18916
Abstract: A reparameterization of the multivariate linear mixed model in genetic evaluation to principal components is described. This yields an equivalent model with a sparser coefficient matrix in the mixed model equations and, thus, reduced computational requirements to solve them. It is especially advantageous for analyses incorporating genomic relationship information with many nonzero elements in the inverse of the relationship matrix. Moreover, the framework lends itself directly to dimension reduction and, thus, further computational savings by omitting genetic principal components with negligible eigenvalues. The potential impact on computational demands is illustrated for an application to single-step genomic evaluation of Australian sheep.
Publication Type: Journal Article
Source of Publication: Journal of Animal Science, 93(10), p. 4624-4628
Publisher: American Society of Animal Science
Place of Publication: Champaign, United States of America
ISSN: 1525-3163
0021-8812
Field of Research (FOR): 070201 Animal Breeding
Socio-Economic Outcome Codes: 830301 Beef Cattle
830399 Livestock Raising not elsewhere classified
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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Appears in Collections:Animal Genetics and Breeding Unit (AGBU)
Journal Article

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