ArticleAnnals of human genetics2012
Bayes factor based on the trend test incorporating Hardy-Weinberg disequilibrium: more power to detect genetic association.
Article in Annals of human genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Bayesian genome- and epigenome-wide association studies with gene level dependence.Biometrics · 2017Article
- Rare high-impact disease variants: properties and identifications.Genetics research · 2016Article
- Bayesian Polynomial Regression Models to Fit Multiple Genetic Models for Quantitative Traits.Bayesian analysis · 2015Article
- A shrinkage method for testing the Hardy-Weinberg equilibrium in case-control studies.Genetic epidemiology · 2013Article
- Incorporating parental information into family-based association tests.Biostatistics (Oxford, England) · 2013Article
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
Abstract
In the analysis of case-control genetic association, the trend test and Pearson's test are the two most commonly used tests. In genome-wide association studies (GWAS), Bayes factor (BF) is a useful tool to support significant P-values, and a better measure than P-value when results are compared across studies with different sample sizes. When reporting the P-value of the trend test, we propose a BF directly based on the trend test. To improve the power to detect association under recessive or dominant genetic models, we propose a BF based on the trend test and incorporating Hardy-Weinberg disequilibrium in cases. When the true model is unknown, or both the trend test and Pearson's test or other robust tests are applied in genome-wide scans, we propose a joint BF, combining the previous two BFs. All three BFs studied in this paper have closed forms and are easy to compute without integrations, so they can be reported along with P-values, especially in GWAS. We discuss how to use each of them and how to specify priors. Simulation studies and applications to three GWAS are provided to illustrate their usefulness to detect nonadditive gene susceptibility in practice.
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Registered trials
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