A mixture model approach for gene selection using Johnson's system and Bayes formula

Microarrays have become increasingly common in biological and medical research. They enable the simultaneous study of thousands of genes and provide gene expression information on a whole genome level. A major goal of microarray experiments is to determine which genes are differentially expressed between samples. A mixed model approach using the Johnson’s system of distributions and Baye’s formula is proposed in this paper for the selection of differentially expressed genes. In this approach, no specific parametric distribution is assumed for the gene expression levels. The simulation results show that the proposed approach has a higher power over the other commonly used Bayesian methods such as EBarrays and EBAM.