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Two-Stage Testing in Microarray Analysis

What Is Gained?

^a Department of Biostatistics, University of Alabama at Birmingham

David B. Allison, Department of Biostatistics, Section on Statistical Genetics, Ryals Bldg, Suite 327, 1665 University Blvd, Birmingham, AL 35294 E-mail: Dallison{at}ms.soph.uab.edu.

Decision Editor: John A. Faulkner, PhD

Microarray technology for gene expression studies offers powerful new technology for understanding changes in gene expression as a function of other observable or manipulable variables. However, microarrays also pose a number of new challenges. One of the most prominent of these is the difficulty in establishing a procedure for declaring whether a gene's expression level is associated with the independent variable that offers reasonable and specifiable false-positive (type 1 error) and false-negative (type 2 error) rates. A recent article described a two-stage testing procedure to address these goals. However, information was not provided to indicate whether this procedure would or would not meet its objectives. Herein, we show mathematically that the two-stage procedure proposed does not provide benefits in terms of minimizing false-negatives while controlling the false-positive rate relative to standard single-stage testing. Therefore, investigators are encouraged to consider alternative analytic approaches.

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				G. L Gadbury, G. P Page, J. Edwards, T. Kayo, T. A Prolla, R. Weindruch, P. A Permana, J. D Mountz, and D. B Allison Power and sample size estimation in high dimensional biology Statistical Methods in Medical Research, August 1, 2004; 13(4): 325 - 338. [Abstract] [PDF]