ArticleThe plant genome2024
A Bayesian optimization R package for multitrait parental selection.
Article in The plant genome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Bayesian divergence-based approach for genomic multitrait ordinal selection.G3 (Bethesda, Md.) · 2025Article
- Haplotype stacking to improve stability of stripe rust resistance in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Optimizing Genomic Parental Selection for Categorical and Continuous-Categorical Multi-Trait Mixtures.Genes · 2024Article
- A Bayesian optimization R package for multitrait parental selection.The plant genome · 2024Article
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7 authors.
Funding
Abstract
Selecting and mating parents in conventional phenotypic and genomic selection are crucial. Plant breeding programs aim to improve the economic value of crops, considering multiple traits simultaneously. When traits are negatively correlated and/or when there are missing records in some traits, selection becomes more complex. To address this problem, we propose a multitrait selection approach using the Multitrait Parental Selection (MPS) R package-an efficient tool for genetic improvement, precision breeding, and conservation genetics. The package employs Bayesian optimization algorithms and three loss functions (Kullback-Leibler, Energy Score, and Multivariate Asymmetric Loss) to identify parental candidates with desirable traits. The software's functionality includes three main functions-EvalMPS, FastMPS, and ApproxMPS-catering to different data availability scenarios. Through the presented application examples, the MPS R package proves effective in multitrait genomic selection, enabling breeders to make informed decisions and achieve strong performance across multiple traits.
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