Approximating prediction error variances and reliabilities in a multiple-trait genomic prediction model using Monte Carlo sampling.

doi:10.1007/s00122-026-05336-0

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Article

Approximating prediction error variances and reliabilities in a multiple-trait genomic prediction model using Monte Carlo sampling.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik - 28 Aug 2026

Heikkilä Antero, Strandén Ismo, Lidauer Martin H, Nordhausen Klaus, Taskinen Sara

Abstract excerpt

KEY MESSAGE: We evaluated four existing Monte Carlo-based methods for approximating prediction error variances and reliabilities in a multiple-trait genomic prediction model. All four methods yielded consistent approximations of the exact values. Genomic prediction models, such as genomic best linear unbiased prediction (GBLUP), use genomic data to improve the accuracy of estimated genetic values. As the number...

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PMID: 42663639
DOI: 10.1007/s00122-026-05336-0
PMCID: PMC13525033

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