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Graphical Exploration of Gene Expression Data: A Comparative Study of Three Multivariate Methods

Author

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  • Luc Wouters
  • Hinrich W. Göhlmann
  • Luc Bijnens
  • Stefan U. Kass
  • Geert Molenberghs
  • Paul J. Lewi

Abstract

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Suggested Citation

  • Luc Wouters & Hinrich W. Göhlmann & Luc Bijnens & Stefan U. Kass & Geert Molenberghs & Paul J. Lewi, 2003. "Graphical Exploration of Gene Expression Data: A Comparative Study of Three Multivariate Methods," Biometrics, The International Biometric Society, vol. 59(4), pages 1131-1139, December.
    • Handle: RePEc:bla:biomet:v:59:y:2003:i:4:p:1131-1139
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2003.00130.x
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    Cited by:

    1. Yvonne Pittelkow & Susan R. Wilson, 2005. "Use of Principal Component Analysis and the GE-Biplot for the Graphical Exploration of Gene Expression Data," Biometrics, The International Biometric Society, vol. 61(2), pages 630-632, June.
    2. Michael Greenacre & Paul Lewi, 2009. "Distributional Equivalence and Subcompositional Coherence in the Analysis of Compositional Data, Contingency Tables and Ratio-Scale Measurements," Journal of Classification, Springer;The Classification Society, vol. 26(1), pages 29-54, April.
    3. Michael Greenacre, 2016. "Selection and statistical analysis of compositional ratios," Economics Working Papers 1551, Department of Economics and Business, Universitat Pompeu Fabra.
    4. Michael Greenacre, 2017. "Towards a pragmatic approach to compositional data analysis," Economics Working Papers 1554, Department of Economics and Business, Universitat Pompeu Fabra.

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