Practical guidelines for assessing power and false discovery rate for a fixed sample size in microarray experiments

Authors

  • Tiejun Tong,

    1. Department of Applied Mathematics, University of Colorado, Boulder, CO 80309, U.S.A.
    Search for more papers by this author
  • Hongyu Zhao

    Corresponding author
    1. Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520, U.S.A.
    2. Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, U.S.A.
    • Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520, U.S.A.
    Search for more papers by this author

Abstract

One major goal in microarray studies is to identify genes having different expression levels across different classes/conditions. In order to achieve this goal, a study needs to have an adequate sample size to ensure the desired power. Owing to the importance of this topic, a number of approaches to sample size calculation have been developed. However, due to the cost and/or experimental difficulties in obtaining sufficient biological materials, it might be difficult to attain the required sample size. In this article, we address more practical questions for assessing power and false discovery rate (FDR) for a fixed sample size. The relationships between power, sample size and FDR are explored. We also conduct simulations and a real data study to evaluate the proposed findings. Copyright © 2008 John Wiley & Sons, Ltd.

Ancillary