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Practical guidelines for assessing power and false discovery rate for a fixed sample size in microarray experiments
Author(s) -
Tong Tiejun,
Zhao Hongyu
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3237
Subject(s) - sample size determination , false discovery rate , sample (material) , computer science , statistical power , multiple comparisons problem , data mining , statistics , power (physics) , mathematics , biology , gene , genetics , chemistry , physics , chromatography , quantum mechanics
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.