ArticleGenetics2010
Nonparametric Bayesian variable selection with applications to multiple quantitative trait loci mapping with epistasis and gene-environment interaction.
Article in Genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- High-Dimensional Gene-Environment Interaction Analysis.Annual review of statistics and its application · 2025Article
- Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues.Human genomics · 2025Review
- Scalable Nonparametric Prescreening Method for Searching Higher-Order Genetic Interactions Underlying Quantitative Traits.Genetics · 2019Article
- A Gaussian process model and Bayesian variable selection for mapping function-valued quantitative traits with incomplete phenotypic data.Bioinformatics (Oxford, England) · 2019Article
- Classification and Clustering Methods for Multiple Environmental Factors in Gene-Environment Interaction: Application to the Multi-Ethnic Study of Atherosclerosis.Epidemiology (Cambridge, Mass.) · 2016Article
- Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures.Biostatistics (Oxford, England) · 2015Article
- Marginally specified priors for non-parametric Bayesian estimation.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2015Article
- ANISOTROPIC FUNCTION ESTIMATION USING MULTI-BANDWIDTH GAUSSIAN PROCESSES.Annals of statistics · 2014Article
- Bayesian Methods for High Dimensional Linear Models.Journal of biometrics & biostatistics · 2013Article
- Review
- Locally Adaptive Bayes Nonparametric Regression via Nested Gaussian Processes.Journal of the American Statistical Association · 2013Article
- Predicting genetic values: a kernel-based best linear unbiased prediction with genomic data.Genetics · 2011Article
- A new mapping method for quantitative trait loci of silkworm.BMC genetics · 2011Article
- Statistical analysis of genetic interactions.Genetics research · 2010Review
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Authors and funding
4 authors.
Funding
Abstract
The joint action of multiple genes is an important source of variation for complex traits and human diseases. However, mapping genes with epistatic effects and gene-environment interactions is a difficult problem because of relatively small sample sizes and very large parameter spaces for quantitative trait locus models that include such interactions. Here we present a nonparametric Bayesian method to map multiple quantitative trait loci (QTL) by considering epistatic and gene-environment interactions. The proposed method is not restricted to pairwise interactions among genes, as is typically done in parametric QTL analysis. Rather than modeling each main and interaction term explicitly, our nonparametric Bayesian method measures the importance of each QTL, irrespective of whether it is mostly due to a main effect or due to some interaction effect(s), via an unspecified function of the genotypes at all candidate QTL. A Gaussian process prior is assigned to this unknown function. In addition to the candidate QTL, nongenetic factors and covariates, such as age, gender, and environmental conditions, can also be included in the unspecified function. The importance of each genetic factor (QTL) and each nongenetic factor/covariate included in the function is estimated by a single hyperparameter, which enters the covariance function and captures any main or interaction effect associated with a given factor/covariate. An initial evaluation of the performance of the proposed method is obtained via analysis of simulated and real data.
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