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Understanding the accuracy of genomic selection

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April 20, 2022

Genomic selection has become the standard tool for genetic improvement of livestock. To optimise their breeding schemes, breeders need to predict the accuracy of genomic selection beforehand. In this publication, Piter Bijma and Jack Dekkers integrate previous expressions for the accuracy of genomic prediction and show that it can be understood as a proportion of the variance explained.

Summary of the article

Deterministic predictions of the accuracy of genomic selection when combining information sources have been developed based on selection index theory and on Fisher information. These two approaches have resulted in slightly different results. In this manuscript, Bijma and Dekkers clarify this apparent contradiction. They show that the squared accuracy of genomic selection can be understood as a proportion of the variance explained, and that the discrepancy between the two approaches disappears when the underlying assumptions are equivalent