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Genomic Best Linear Unbiased Prediction (gBLUP) for the Estimation of Genomic Breeding Values

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Book cover Genome-Wide Association Studies and Genomic Prediction

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1019))

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.

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Clark, S.A., van der Werf, J. (2013). Genomic Best Linear Unbiased Prediction (gBLUP) for the Estimation of Genomic Breeding Values. In: Gondro, C., van der Werf, J., Hayes, B. (eds) Genome-Wide Association Studies and Genomic Prediction. Methods in Molecular Biology, vol 1019. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-447-0_13

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  • DOI: https://doi.org/10.1007/978-1-62703-447-0_13

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-446-3

  • Online ISBN: 978-1-62703-447-0

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