ArticleBiometrics2014
Bayesian model selection in complex linear systems, as illustrated in genetic association studies.
Article in Biometrics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Meta-Analysis of SNP-Environment Interaction With Overlapping Data.Frontiers in genetics · 2019Article
- A Bayesian group sparse multi-task regression model for imaging genetics.Bioinformatics (Oxford, England) · 2017Article
- Efficient Integrative Multi-SNP Association Analysis via Deterministic Approximation of Posteriors.American journal of human genetics · 2016Article
- Perinatal Lead Exposure Alters Gut Microbiota Composition and Results in Sex-specific Bodyweight Increases in Adult Mice.Toxicological sciences : an official journal of the Society of Toxicology · 2016Article
- A general framework for meta-analyzing dependent studies with overlapping subjects in association mapping.Human molecular genetics · 2016Article
- A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.Nature genetics · 2016Article
- Strategies for fine-mapping complex traits.Human molecular genetics · 2015Review
- Bayesian model comparison in genetic association analysis: linear mixed modeling and SNP set testing.Biostatistics (Oxford, England) · 2015Article
- Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics.Genetics · 2015Article
- Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans.Science (New York, N.Y.) · 2015Article
- Cross-population joint analysis of eQTLs: fine mapping and functional annotation.PLoS genetics · 2015Article
Corrections and comments
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1 author.
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Abstract
Motivated by examples from genetic association studies, this article considers the model selection problem in a general complex linear model system and in a Bayesian framework. We discuss formulating model selection problems and incorporating context-dependent a priori information through different levels of prior specifications. We also derive analytic Bayes factors and their approximations to facilitate model selection and discuss their theoretical and computational properties. We demonstrate our Bayesian approach based on an implemented Markov Chain Monte Carlo (MCMC) algorithm in simulations and a real data application of mapping tissue-specific eQTLs. Our novel results on Bayes factors provide a general framework to perform efficient model comparisons in complex linear model systems.
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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.