Curbing false discovery rates in interpretation of genome-wide expression profiles

Abstract

Fisher's exact test is widely used in biomedical research, particularly in genomic profile analysis. Since in most databases, the frequency distribution of genes is right skewed, we show here that its use can lead to excessive false-positive discoveries. We propose to apply Zelen's exact test on a stratification of the gene set; this solves the false discovery problem, and should avoid misleading interpretations of lists of genes produced by various genome-wide analysis technologies.

Keywords: Genomics; Statistics; Transcriptomics.