CRAN/E | roben

roben

Robust Bayesian Variable Selection for Gene-Environment Interactions

Installation

About

Gene-environment (G×E) interactions have important implications to elucidate the etiology of complex diseases beyond the main genetic and environmental effects. Outliers and data contamination in disease phenotypes of G×E studies have been commonly encountered, leading to the development of a broad spectrum of robust penalization methods. Nevertheless, within the Bayesian framework, the issue has not been taken care of in existing studies. We develop a robust Bayesian variable selection method for G×E interaction studies. The proposed Bayesian method can effectively accommodate heavy-tailed errors and outliers in the response variable while conducting variable selection by accounting for structural sparsity. In particular, the spike-and-slab priors have been imposed on both individual and group levels to identify important main and interaction effects. An efficient Gibbs sampler has been developed to facilitate fast computation. The Markov chain Monte Carlo algorithms of the proposed and alternative methods are efficiently implemented in C++.

github.com/jrhub/roben
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Key Metrics

Version 0.1.1
R ≥ 4.0.0
Published 2024-03-12 211 days ago
Needs compilation? yes
License GPL-2
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Maintainer

Maintainer

Jie Ren

Authors

Jie Ren
Fei Zhou
Xiaoxi Li
Cen Wu

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

roben archive

Depends

R ≥ 4.0.0

Imports

Rcpp
glmnet
stats

Suggests

testthat ≥ 3.0.0
covr

LinkingTo

Rcpp
RcppArmadillo