marble

Robust Marginal Bayesian Variable Selection for Gene-Environment Interactions

CRAN Package

Recently, multiple marginal variable selection methods have been developed and shown to be effective in Gene-Environment interactions studies. We propose a novel marginal Bayesian variable selection method for Gene-Environment interactions studies. In particular, our marginal Bayesian method is robust to data contamination and outliers in the outcome variables. With the incorporation of spike-and-slab priors, we have implemented the Gibbs sampler based on Markov Chain Monte Carlo. The core algorithms of the package have been developed in 'C++'.

  • Version0.0.3
  • R versionunknown
  • LicenseGPL-2
  • Needs compilation?Yes
  • Last release04/04/2024

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