Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/746
Title: | Direct Estimation of Genetic Principal Components: Simplified Analysis of Complex Phenotypes | Contributor(s): | Kirkpatrick, M (author); Meyer, K (author) | Publication Date: | 2004 | DOI: | 10.1534/genetics.104.029181 | Handle Link: | https://hdl.handle.net/1959.11/746 | Abstract: | Estimating the genetic and environmental variances for multivariate and function-valued phenotypes poses problems for estimation and interpretation. Even when the phenotype of interest has a large number of dimensions, most variation is typically associated with a small number of principal components (eigenvectors or eigenfunctions). We propose an approach that directly estimates these leading principal components; these then give estimates for the covariance matrices (or functions). Direct estimation of the principal components reduces the number of parameters to be estimated, uses the data efficiently, and provides the basis for new estimation algorithms. We develop these concepts for both multivariate and function-valued phenotypes and illustrate their application in the restricted maximum-likelihood framework. | Publication Type: | Journal Article | Source of Publication: | Genetics, 168(4), p. 2295-2306 | Publisher: | Genetics Society of America | Place of Publication: | United States of America | ISSN: | 1943-2631 0016-6731 |
Fields of Research (FoR) 2008: | 070201 Animal Breeding | Peer Reviewed: | Yes | HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
---|---|
Appears in Collections: | Animal Genetics and Breeding Unit (AGBU) Journal Article |
Files in This Item:
File | Description | Size | Format |
---|
SCOPUSTM
Citations
118
checked on Apr 6, 2024
Page view(s)
1,048
checked on Jun 18, 2023
Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.