Improving type II error rates of multiple testing procedures by use of auxiliary variables Application to microarray data

Simultaneous tests of a huge number of hypotheses is a core issue in high flow experimental methods. In the central debate about the type I error rate, [Benjamini and Hochberg, 1995] have provided a procedure that controls the now popular False Discovery Rate (FDR).

The present paper focuses on the type II error rate. The proposed strategy improves the power by means of moderated test statistics integrating external information available in a double-sampling scheme. The small sample distribution of the test statistics is provided. Finally, the present method is implemented on transcriptomic data.