ArticleFrontiers in genetics2018
Prediction of Complex Traits: Robust Alternatives to Best Linear Unbiased Prediction.
Article in Frontiers in genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Multi-metric evaluation and parametric optimization of stochastic gradient boosting machines for genomic prediction and selection in wheat (Triticum aestivum) breeding.G3 (Bethesda, Md.) · 2026Article
- 2NPLGBM: a genomic model that merges the strengths of classical and machine learning methods in genomic prediction.Plant methods · 2026Article
- Normalized cumulative gain as an alternative evaluation measure for genomic selection models.Genetics, selection, evolution : GSE · 2025Article
- Local and Bayesian Survival FDR Estimations to Identify Reliable Associations in Whole Genome of Bread Wheat.International journal of molecular sciences · 2023Article
- Inference about quantitative traits under selection: a Bayesian revisitation for the post-genomic era.Genetics, selection, evolution : GSE · 2022Article
- Heterosis and Hybrid Crop Breeding: A Multidisciplinary Review.Frontiers in genetics · 2021Review
- A Multiple-Trait Bayesian Lasso for Genome-Enabled Analysis and Prediction of Complex Traits.Genetics · 2020Article
- A robust Bayesian genome-based median regression model.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019Article
- Bayesian, Likelihood-Free Modelling of Phenotypic Plasticity and Variability in Individuals and Populations.Frontiers in genetics · 2019Article
- Phenotypic Selection in Ornamental Breeding: It's Better to Have the BLUPs Than to Have the BLUEs.Frontiers in plant science · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A widely used method for prediction of complex traits in animal and plant breeding is "genomic best linear unbiased prediction" (GBLUP). In a quantitative genetics setting, BLUP is a linear regression of phenotypes on a pedigree or on a genomic relationship matrix, depending on the type of input information available. Normality of the distributions of random effects and of model residuals is not required for BLUP but a Gaussian assumption is made implicitly. A potential downside is that Gaussian linear regressions are sensitive to outliers, genetic or environmental in origin. We present simple (relative to a fully Bayesian analysis) to implement robust alternatives to BLUP using a linear model with residual
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