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Bayesian Methods for Genomic Prediction and Genome-Wide Association Studies combining Information on Genotyped and Non-Genotyped Individuals

Authors: Rohan L Fernando (Iowa State University) , Jack C. M. Dekkers (Iowa State University) , Dorian J. Garrick (Iowa State University)

Abstract

Genomic prediction involves using high-density marker genotypes to characterize the impact on performance of every region of the genome, and using that information to predict performance of genotyped selection candidates. This is a relatively new technology and is now gaining traction in personalized medicine and in various livestock industries. Our new approach promises to overcome serious limitations with existing techniques for genomic prediction.

Keywords: Animal Science

How to Cite: Fernando, R. L. , Dekkers, J. C. & Garrick, D. J. (2014) “Bayesian Methods for Genomic Prediction and Genome-Wide Association Studies combining Information on Genotyped and Non-Genotyped Individuals”, Iowa State University Animal Industry Report. 11(1). doi: https://doi.org/10.31274/ans_air-180814-1245