FEBS Letters
Volume 584, Issue 5 , Pages 941-944, 5 March 2010

Comments on the rank product method for analyzing replicated experiments

Edited by Takashi Gojobori

Department of Molecular and Experimental Medicine, The Scripps Research Institute, MEM216, 10550 N Torrey Pines Rd, La Jolla, CA 92037, USA

Received 31 December 2009; accepted 14 January 2010. published online 20 January 2010.

Abstract 

Breitling et al. [1] introduced a statistical technique, the rank product method, for detecting differentially regulated genes in replicated microarray experiments. The technique has achieved widespread acceptance and is now used more broadly, in such diverse fields as RNAi analysis, proteomics, and machine learning. In this note, we relate the rank product method to linear rank statistics and provide an alternative derivation of distribution theory attending the rank product method.

Keywords: Rank product method, Rank statistics, Wilcoxon score, van der Waerden score, Gamma approximation, Edgeworth approximation

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PII: S0014-5793(10)00054-2

doi:10.1016/j.febslet.2010.01.031

FEBS Letters
Volume 584, Issue 5 , Pages 941-944, 5 March 2010