Introduction

Accurate and rapid identification of perturbed pathways through the analysis of genome-wide expression profiles facilitates the generation of biological hypotheses. We propose a statistical framework for determining whether a specified group of genes for a pathway has a coordinated association with a phenotype of interest. Several issues on proper hypothesis-testing procedures are clarified. In particular, it is shown that the differences in the correlation structure of each set of genes can lead to a biased comparison among gene sets unless a normalization procedure is applied. We propose statistical tests for two important but different aspects of association for each group of genes. This approach has more statistical power than currently available methods and can result in the discovery of statistically significant pathways that are not detected by other methods. This method is applied to data sets involving diabetes, inflammatory myopathies, and Alzheimer's disease, using gene sets we compiled from various public databases. In the case of inflammatory myopathies, we have correctly identified the known cytotoxic T lymphocyte-mediated autoimmunity in inclusion body myositis. Furthermore, we predicted the presence of dendritic cells in inclusion body myositis and of an IFN-alpha/beta response in dermatomyositis, neither of which was previously described. These predictions have been subsequently corroborated by immunohistochemistry.

Publications

  1. Discovering statistically significant pathways in expression profiling studies.
    Cite this
    Tian L, Greenberg SA, Kong SW, Altschuler J, Kohane IS, Park PJ, 2005-09-01 - Proceedings of the National Academy of Sciences of the United States of America

Credits

  1. Lu Tian
    Developer

    Department of Preventive Medicine, Feinberg School of Medicine, United States of America

  2. Steven A Greenberg
    Developer

  3. Sek Won Kong
    Developer

  4. Josiah Altschuler
    Developer

  5. Isaac S Kohane
    Developer

  6. Peter J Park
    Investigator

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Summary
AccessionBT001663
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Submitted ByPeter J Park