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)![]() ![]() |
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: | United States of America | ISSN: | 1525-3163 0021-8812 |
Fields of Research (FoR) 2008: | 070201 Animal Breeding | Fields of Research (FoR) 2020: | 300305 Animal reproduction and breeding | Socio-Economic Objective (SEO) 2008: | 830301 Beef Cattle 830399 Livestock Raising not elsewhere classified |
Socio-Economic Objective (SEO) 2020: | 100401 Beef cattle | 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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