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Covariance-based analyses of biological pathways

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  • P. Danaher
  • D. Paul
  • P. Wang

Abstract

The use of high-throughput data to study the changing behaviour of biological pathways has focused mainly on examining the changes in the means of pathway genes. In this paper, we propose instead to test for changes in the co-regulated and unregulated variability of pathway genes. We assume that the eigenvalues of previously defined pathways capture biologically relevant quantities, and we develop a test for biologically meaningful changes in the eigenvalues between classes. This test reflects important and often ignored aspects of pathway behaviour and provides a useful complement to traditional pathway analyses.

Suggested Citation

  • P. Danaher & D. Paul & P. Wang, 2015. "Covariance-based analyses of biological pathways," Biometrika, Biometrika Trust, vol. 102(3), pages 533-544.
    • Handle: RePEc:oup:biomet:v:102:y:2015:i:3:p:533-544.
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    File URL: http://hdl.handle.net/10.1093/biomet/asv013
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    Cited by:

    1. Jodi M. Carter & Saranya Chumsri & Douglas A. Hinerfeld & Yaohua Ma & Xue Wang & David Zahrieh & David W. Hillman & Kathleen S. Tenner & Jennifer M. Kachergus & Heather Ann Brauer & Sarah E. Warren & , 2023. "Distinct spatial immune microlandscapes are independently associated with outcomes in triple-negative breast cancer," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

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