The exact probability distribution of the rank product statistics for replicated experiments

Rob Eisinga, Rainer Breitling, Tom Heskes

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The rank product method is a widely accepted technique for detecting differentially regulated genes in replicated microarray experiments. To approximate the sampling distribution of the rank product statistic, the original publication proposed a permutation approach, whereas recently an alternative approximation based on the continuous gamma distribution was suggested. However, both approximations are imperfect for estimating small tail probabilities. In this paper we relate the rank product statistic to number theory and provide a derivation of its exact probability distribution and the true tail probabilities. © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
    Original languageEnglish
    Pages (from-to)677-682
    Number of pages5
    JournalFEBS Letters
    Volume587
    Issue number6
    DOIs
    Publication statusPublished - 18 Mar 2013

    Keywords

    • Exact inference
    • Gamma approximation
    • Microarray
    • Permutational inference
    • Rank product method

    Fingerprint

    Dive into the research topics of 'The exact probability distribution of the rank product statistics for replicated experiments'. Together they form a unique fingerprint.

    Cite this