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|Title:||Genomic Best Linear Unbiased Prediction (gBLUP) for the Estimation of Genomic Breeding Values||Contributor(s):||Clark, Sam A (author) ; Van Der Werf, Julius H (author)||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
|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||Statistics to Oct 2018:||Visitors: 193
|Appears in Collections:||Book Chapter|
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