ArticleGenetics2012
Estimation of quantitative trait locus effects with epistasis by variational Bayes algorithms.
Article in Genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Applying gradient tree boosting to QTL mapping with Shapley additive explanations.Breeding science · 2025Article
- Local and Bayesian Survival FDR Estimations to Identify Reliable Associations in Whole Genome of Bread Wheat.International journal of molecular sciences · 2023Article
- An approximate Bayesian significance test for genomic evaluations.Biometrical journal. Biometrische Zeitschrift · 2018Article
- Detection of Epistasis for Flowering Time Using Bayesian Multilocus Estimation in a Barley MAGIC Population.Genetics · 2018Article
- A fast algorithm for Bayesian multi-locus model in genome-wide association studies.Molecular genetics and genomics : MGG · 2017Article
- A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction.G3 (Bethesda, Md.) · 2017Article
- Toward integration of genomic selection with crop modelling: the development of an integrated approach to predicting rice heading dates.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2016Article
- An Efficient Genome-Wide Multilocus Epistasis Search.Genetics · 2015Article
- Prediction of complex human diseases from pathway-focused candidate markers by joint estimation of marker effects: case of chronic fatigue syndrome.Human genomics · 2015Article
- Exploring the areas of applicability of whole-genome prediction methods for Asian rice (Oryza sativa L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2015Article
- A Ranking Approach to Genomic Selection.PloS one · 2015Article
- Article
- Comparison of single-trait and multiple-trait genomic prediction models.BMC genetics · 2014Article
- A variational Bayes discrete mixture test for rare variant association.Genetic epidemiology · 2014Article
- Article
- A Bayesian method and its variational approximation for prediction of genomic breeding values in multiple traits.BMC bioinformatics · 2013Article
- A decision rule for quantitative trait locus detection under the extended Bayesian LASSO model.Genetics · 2012Article
- Swift block-updating EM and pseudo-EM procedures for Bayesian shrinkage analysis of quantitative trait loci.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012Article
- Genomic prediction of hybrid performance in maize with models incorporating dominance and population specific marker effects.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012Article
- Overview of LASSO-related penalized regression methods for quantitative trait mapping and genomic selection.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012Review
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2 authors.
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Abstract
Bayesian hierarchical shrinkage methods have been widely used for quantitative trait locus mapping. From the computational perspective, the application of the Markov chain Monte Carlo (MCMC) method is not optimal for high-dimensional problems such as the ones arising in epistatic analysis. Maximum a posteriori (MAP) estimation can be a faster alternative, but it usually produces only point estimates without providing any measures of uncertainty (i.e., interval estimates). The variational Bayes method, stemming from the mean field theory in theoretical physics, is regarded as a compromise between MAP and MCMC estimation, which can be efficiently computed and produces the uncertainty measures of the estimates. Furthermore, variational Bayes methods can be regarded as the extension of traditional expectation-maximization (EM) algorithms and can be applied to a broader class of Bayesian models. Thus, the use of variational Bayes algorithms based on three hierarchical shrinkage models including Bayesian adaptive shrinkage, Bayesian LASSO, and extended Bayesian LASSO is proposed here. These methods performed generally well and were found to be highly competitive with their MCMC counterparts in our example analyses. The use of posterior credible intervals and permutation tests are considered for decision making between quantitative trait loci (QTL) and non-QTL. The performance of the presented models is also compared with R/qtlbim and R/BhGLM packages, using a previously studied simulated public epistatic data set.
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