ArticleGenetics2013
Priors in whole-genome regression: the bayesian alphabet returns.
Article in Genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 246 papers, 1 of them a synthesis that pooled it.
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246 citing papers in PubMed, 1 synthesis or guideline pooled it, 469 citations in OpenAlex.
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- Impact of scale parameter for marker variance prior in some Bayesian whole-genome regression methods.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- A Flexible Method for Genomics-Based Quantitative Genetics in Wild Study Systems-A Case Study on a House Sparrow Meta-Population.Evolutionary applications · 2026Article
- MeNet: A mixed-effect deep neural network for multi-environment genomic prediction of agronomic traits.Plant communications · 2026Article
- Sharing approaches in predictive genomics across animals, plants and humans.Nature genetics · 2026Review
- Opportunities and computational challenges in large-scale whole-genome sequencing data analysis.Journal of animal science · 2026Review
- Different approaches for estimating the shrinkage factor in ridge regression BLUP for genomic selection.Scientific reports · 2025Article
- First development of a 100 K SNP array for small yellow croaker and its application in genomic selection for growth and disease resistance.BMC genomics · 2025Article
- Advancements in Animal Breeding: From Mendelian Genetics to Machine Learning.International journal of molecular sciences · 2025Review
- Integrative Machine Learning Approaches for Identifying Loci Associated with Anthracnose Resistance in Strawberry.Plants (Basel, Switzerland) · 2025Article
- Ensemble of Bayesian alphabets via constraint weight optimization strategy improves genomic prediction accuracy.G3 (Bethesda, Md.) · 2025Article
- Genomic Prediction of Adaptation in Common Bean (International journal of molecular sciences · 2025Article
- Bivariate GWAS performed on rabbits divergently selected for intramuscular fat content reveals pleiotropic genomic regions and genes related to meat and carcass quality traits.Genetics, selection, evolution : GSE · 2025Article
- Breaking down data silos across companies to train genome-wide predictions: A feasibility study in wheat.Plant biotechnology journal · 2025Article
- Variable selection strategies for genomic prediction of growth and carcass related traits in experimental Nellore cattle herds under different selection criteria.Scientific reports · 2025Article
- Genotype-by-environment interaction with high-dimensional environmental data: an example in pigs.Genetics, selection, evolution : GSE · 2025Article
- Genomic selection: Essence, applications, and prospects.The plant genome · 2025Review
186 more citing papers are in PubMed but not listed here.
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1 author at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Whole-genome enabled prediction of complex traits has received enormous attention in animal and plant breeding and is making inroads into human and even Drosophila genetics. The term "Bayesian alphabet" denotes a growing number of letters of the alphabet used to denote various Bayesian linear regressions that differ in the priors adopted, while sharing the same sampling model. We explore the role of the prior distribution in whole-genome regression models for dissecting complex traits in what is now a standard situation with genomic data where the number of unknown parameters (p) typically exceeds sample size (n). Members of the alphabet aim to confront this overparameterization in various manners, but it is shown here that the prior is always influential, unless n ≫ p. This happens because parameters are not likelihood identified, so Bayesian learning is imperfect. Since inferences are not devoid of the influence of the prior, claims about genetic architecture from these methods should be taken with caution. However, all such procedures may deliver reasonable predictions of complex traits, provided that some parameters ("tuning knobs") are assessed via a properly conducted cross-validation. It is concluded that members of the alphabet have a room in whole-genome prediction of phenotypes, but have somewhat doubtful inferential value, at least when sample size is such that n ≪ p.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.