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Testing for pathway (in)activation by using Gaussian graphical models

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  • Wessel N. van Wieringen
  • Carel F. W. Peeters
  • Renee X. de Menezes
  • Mark A. van de Wiel

Abstract

Genes work together in sets known as pathways to contribute to cellular processes, such as apoptosis and cell proliferation. Pathway activation, or inactivation, may be reflected in varying partial correlations between the levels of expression of the genes that constitute the pathway. Here we present a method to identify pathway activation status from two‐sample studies. By modelling the levels of expression in each group by using a Gaussian graphical model, their partial correlations are proportional, differing by a common multiplier that reflects the activation status. We estimate model parameters by means of penalized maximum likelihood and evaluate the estimation procedure performance in a simulation study. A permutation scheme to test for pathway activation status is proposed. A reanalysis of publicly available data on the hedgehog pathway in normal and cancer prostate tissue shows its activation in the disease group: an indication that this pathway is involved in oncogenesis. Extensive diagnostics employed in the reanalysis complete the methodology proposed.

Suggested Citation

  • Wessel N. van Wieringen & Carel F. W. Peeters & Renee X. de Menezes & Mark A. van de Wiel, 2018. "Testing for pathway (in)activation by using Gaussian graphical models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1419-1436, November.
    • Handle: RePEc:bla:jorssc:v:67:y:2018:i:5:p:1419-1436
    DOI: 10.1111/rssc.12282
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    References listed on IDEAS

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    1. van Wieringen, Wessel N. & Stam, Koen A. & Peeters, Carel F.W. & van de Wiel, Mark A., 2020. "Updating of the Gaussian graphical model through targeted penalized estimation," Journal of Multivariate Analysis, Elsevier, vol. 178(C).

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