A gene-by-gene multiple comparison analysis: A predictive Bayesian approach

Abstract

In this paper, we propose a hierarchical Bayesian framework with a prior Dirichlet process for gene-by-gene multiple comparison analysis. The comparison among experimental conditions are made using the posterior probability for hypothesis of equality or inequality. To calculate the posterior probabilities, we use the Polya urn scheme through latent variables and the Bayes factor. The performance of the proposed method, as well as a comparison with usual Tukey-test, are evaluated on artificial data and on a shotgun proteomics data set. The results reveal a better performance of the proposed methodology in identification of difference of means and/or variance.