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Assessing Statistical Significance in Microarray Experiments Using the Distance Between Microarrays

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  • Douglas Hayden
  • Peter Lazar
  • David Schoenfeld
  • for The Inflammation and the Host Response to Injury Investigators

Abstract

We propose permutation tests based on the pairwise distances between microarrays to compare location, variability, or equivalence of gene expression between two populations. For these tests the entire microarray or some pre-specified subset of genes is the unit of analysis. The pairwise distances only have to be computed once so the procedure is not computationally intensive despite the high dimensionality of the data. An R software package, permtest, implementing the method is freely available from the Comprehensive R Archive Network at http://cran.r-project.org.

Suggested Citation

  • Douglas Hayden & Peter Lazar & David Schoenfeld & for The Inflammation and the Host Response to Injury Investigators, 2009. "Assessing Statistical Significance in Microarray Experiments Using the Distance Between Microarrays," PLOS ONE, Public Library of Science, vol. 4(6), pages 1-7, June.
    • Handle: RePEc:plo:pone00:0005838
    DOI: 10.1371/journal.pone.0005838
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    Cited by:

    1. Alberto Muñoz & Gabriel Martos & Javier Gonzalez, 2023. "Level Sets Semimetrics for Probability Measures with Applications in Hypothesis Testing," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-17, March.

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