ArticleBMC bioinformatics2010
A variational Bayes algorithm for fast and accurate multiple locus genome-wide association analysis.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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Who cites it
47 citing papers in PubMed.
- Is Seeing Believing? A Practitioner's Perspective on High-Dimensional Statistical Inference in Cancer Genomics Studies.Entropy (Basel, Switzerland) · 2024Review
- BLUPmrMLM: A Fast mrMLM Algorithm in Genome-wide Association Studies.Genomics, proteomics & bioinformatics · 2024Article
- Finemap-MiXeR: A variational Bayesian approach for genetic finemapping.PLoS genetics · 2024Article
- A flexible empirical Bayes approach to multivariate multiple regression, and its improved accuracy in predicting multi-tissue gene expression from genotypes.PLoS genetics · 2023Article
- Fast and accurate Bayesian polygenic risk modeling with variational inference.American journal of human genetics · 2023Article
- A Poisson reduced-rank regression model for association mapping in sequencing data.BMC bioinformatics · 2022Article
- Identification of Loci Governing Agronomic Traits and Mutation Hotspots via a GBS-Based Genome-Wide Association Study in a Soybean Mutant Diversity Pool.International journal of molecular sciences · 2022Article
- Variational Bayes for high-dimensional proportional hazards models with applications within gene expression.Bioinformatics (Oxford, England) · 2022Article
- False discovery rate control in genome-wide association studies with population structure.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Improving Quantitative Traits in Self-Pollinated Crops Using Simulation-Based Selection With Minimal Crossing.Frontiers in plant science · 2021Article
- A simple new approach to variable selection in regression, with application to genetic fine mapping.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2020Article
- Inferring Gene-by-Environment Interactions with a Bayesian Whole-Genome Regression Model.American journal of human genetics · 2020Article
- KAML: improving genomic prediction accuracy of complex traits using machine learning determined parameters.Genome biology · 2020Article
- Statistical methods for SNP heritability estimation and partition: A review.Computational and structural biotechnology journal · 2020Review
- Biological and practical implications of genome-wide association study of schizophrenia using Bayesian variable selection.NPJ schizophrenia · 2019Article
- Distinct epigenetic profiles in children with perinatally-acquired HIV on antiretroviral therapy.Scientific reports · 2019Article
- Korean soybean core collection: Genotypic and phenotypic diversity population structure and genome-wide association study.PloS one · 2019Article
- An approximate Bayesian significance test for genomic evaluations.Biometrical journal. Biometrische Zeitschrift · 2018Article
- LPG: A four-group probabilistic approach to leveraging pleiotropy in genome-wide association studies.BMC genomics · 2018Article
- Detection of Epistasis for Flowering Time Using Bayesian Multilocus Estimation in a Barley MAGIC Population.Genetics · 2018Article
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3 authors.
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Abstract
backgroundThe success achieved by genome-wide association (GWA) studies in the identification of candidate loci for complex diseases has been accompanied by an inability to explain the bulk of heritability. Here, we describe the algorithm V-Bay, a variational Bayes algorithm for multiple locus GWA analysis, which is designed to identify weaker associations that may contribute to this missing heritability.
resultsV-Bay provides a novel solution to the computational scaling constraints of most multiple locus methods and can complete a simultaneous analysis of a million genetic markers in a few hours, when using a desktop. Using a range of simulated genetic and GWA experimental scenarios, we demonstrate that V-Bay is highly accurate, and reliably identifies associations that are too weak to be discovered by single-marker testing approaches. V-Bay can also outperform a multiple locus analysis method based on the lasso, which has similar scaling properties for large numbers of genetic markers. For demonstration purposes, we also use V-Bay to confirm associations with gene expression in cell lines derived from the Phase II individuals of HapMap.
conclusionsV-Bay is a versatile, fast, and accurate multiple locus GWA analysis tool for the practitioner interested in identifying weaker associations without high false positive rates.
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