Over the past 10 years, the development of microarray biotechnology has become a popular and powerful tool in understanding biological processes at a molecular level . Microarray technology allows for the simultaneous study of thousands of genes in an automated setting. These highthroughput assays are critical in a number of biomedical applications such as cancer classi cation , disease diagnosis , and drug discovery . At the same time, there has been a call for innovation in the statistical science discipline to develop a new methodology to analyze these complex and high-dimensional genomic assays. Several statistical areas where we have witnessed increased
development include multiple comparisons and testing [5,6], high-dimensional data analyses , machine-learning techniques , Bayesian methods [9,10], and the design of experiments .