Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/14597
Title: Genomic Best Linear Unbiased Prediction (gBLUP) for the Estimation of Genomic Breeding Values
Contributor(s): Clark, Sam A  (author)orcid ; Van Der Werf, Julius H  (author)orcid 
Publication Date: 2013
DOI: 10.1007/978-1-62703-447-0_13
Handle Link: https://hdl.handle.net/1959.11/14597
Abstract: Genomic best linear unbiased prediction (gBLUP) is a method that utilizes genomic relationships to estimate the genetic merit of an individual. For this purpose, a genomic relationship matrix is used, estimated from DNA marker information. The matrix defines the covariance between individuals based on observed similarity at the genomic level, rather than on expected similarity based on pedigree, so that more accurate predictions of merit can be made. gBLUP has been used for the prediction of merit in livestock breeding, may also have some applications to the prediction of disease risk, and is also useful in the estimation of variance components and genomic heritabilities.
Publication Type: Book Chapter
Source of Publication: Genome-Wide Association Studies and Genomic Prediction, p. 321-330
Publisher: Humana Press
Place of Publication: New York, United States of America
ISBN: 9781627034470
9781627034463
Field of Research (FOR): 060412 Quantitative Genetics (incl Disease and Trait Mapping Genetics)
HERDC Category Description: B1 Chapter in a Scholarly Book
Other Links: http://trove.nla.gov.au/version/198468706
Series Name: Methods in Molecular Biology
Series Number : 1019
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Appears in Collections:Book Chapter

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