Estimation in a multiplicative mixed model involving a genetic relationship matrix

Kelly, Alison M., Cullis, Brian R., Gilmour, Arthur R., Eccleston, John A. and Thompson, Robin (2009) Estimation in a multiplicative mixed model involving a genetic relationship matrix. Genetics Selection Evolution, 41 33: 1-9. doi:10.1186/1297-9686-41-33


Author Kelly, Alison M.
Cullis, Brian R.
Gilmour, Arthur R.
Eccleston, John A.
Thompson, Robin
Title Estimation in a multiplicative mixed model involving a genetic relationship matrix
Journal name Genetics Selection Evolution   Check publisher's open access policy
ISSN 0999-193X
1297-9686
Publication date 2009-04-09
Sub-type Article (original research)
DOI 10.1186/1297-9686-41-33
Open Access Status DOI
Volume 41
Issue 33
Start page 1
End page 9
Total pages 9
Place of publication London, U.K.
Publisher BioMed Central
Language eng
Formatted abstract
Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.
Keyword Numerator relationship matrix
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Physical Sciences Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 9 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 14 times in Scopus Article | Citations
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Created: Thu, 03 Sep 2009, 07:57:28 EST by Mr Andrew Martlew on behalf of School of Mathematics & Physics