Two-stage false discovery rate in microarray studies

Abstract

In microarray and other genomic studies, in view of an abundance of genes, one statistical approach is to hold the family wise error rate to a prescribed limit while controlling the false discovery rate by suitable multiple hypothesis testing procedures, thus generally compromising the power properties to a certain extent. Since the genes are not generally independent or even marginally identically distributed, model flexibility is an essential task regardless of dependent structures among genes. In this respect, incorporating a version of the Chen-Stein theorem, two-stage procedure has been considered; it seems to have better average power without much elevation of false discovery rate compared to single-stage procedure. Simulation studies and applications in microarray data models are also stressed with the methodological developments.

Keywords:

• Microarray data
• false discovery rate
• Poisson approximation
• average power

Additional information

Funding

This work was supported by the Research Institute of Natural Science of Gangneung-Wonju National University.