Biostatistics Vol. 6 No. 1 © Oxford University Press 2005; all rights reserved.
Sample size determination in microarray experiments for class comparison and prognostic classification
Biometric Research Branch, National Cancer Institute, 6130 Executive Blvd., Bethesda, MD, 20892-7434, USA dobbinke{at}mail.nih.gov
Determining sample sizes for microarray experiments is important but the complexity of these experiments, and the large amounts of data they produce, can make the sample size issue seem daunting, and tempt researchers to use rules of thumb in place of formal calculations based on the goals of the experiment. Here we present formulae for determining sample sizes to achieve a variety of experimental goals, including class comparison and the development of prognostic markers. Results are derived which describe the impact of pooling, technical replicates and dye-swap arrays on sample size requirements. These results are shown to depend on the relative sizes of different sources of variability. A variety of common types of experimental situations and designs used with single-label and dual-label microarrays are considered. We discuss procedures for controlling the false discovery rate. Our calculations are based on relatively simple yet realistic statistical models for the data, and provide straightforward sample size calculation formulae.
Keywords: Experimental design; Gene expression; Microarrays; Sample size
![]()
CiteULike
Connotea
Del.icio.us What's this?
This article has been cited by other articles:
![]() |
D. N. Grigoryev, M. Liu, H. T. Hassoun, C. Cheadle, K. C. Barnes, and H. Rabb The Local and Systemic Inflammatory Transcriptome after Acute Kidney Injury J. Am. Soc. Nephrol., March 1, 2008; 19(3): 547 - 558. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. A. Sparano and S. Paik Development of the 21-Gene Assay and Its Application in Clinical Practice and Clinical Trials J. Clin. Oncol., February 10, 2008; 26(5): 721 - 728. [Abstract] [Full Text] [PDF] |
||||
![]() |
K. K. Dobbin, Y. Zhao, and R. M. Simon How Large a Training Set is Needed to Develop a Classifier for Microarray Data? Clin. Cancer Res., January 1, 2008; 14(1): 108 - 114. [Abstract] [Full Text] [PDF] |
||||
![]() |
H. T. Hassoun, D. N. Grigoryev, M. L. Lie, M. Liu, C. Cheadle, R. M. Tuder, and H. Rabb Ischemic acute kidney injury induces a distant organ functional and genomic response distinguishable from bilateral nephrectomy Am J Physiol Renal Physiol, July 1, 2007; 293(1): F30 - F40. [Abstract] [Full Text] [PDF] |
||||
![]() |
P. Liu and J. T. G. Hwang Quick calculation for sample size while controlling false discovery rate with application to microarray analysis Bioinformatics, March 15, 2007; 23(6): 739 - 746. [Abstract] [Full Text] [PDF] |
||||
![]() |
K. K. Dobbin and R. M. Simon Sample size planning for developing classifiers using high-dimensional DNA microarray data Biostat., January 1, 2007; 8(1): 101 - 117. [Abstract] [Full Text] [PDF] |
||||
![]() |
G. J. M. Rosa, N. de Leon, and A. J. M. Rosa Review of microarray experimental design strategies for genetical genomics studies Physiol Genomics, December 13, 2006; 28(1): 15 - 23. [Abstract] [Full Text] [PDF] |
||||
![]() |
B. A. Simon, R. B. Easley, D. N. Grigoryev, S.-F. Ma, S. Q. Ye, T. Lavoie, R. M. Tuder, and J. G. N. Garcia Microarray analysis of regional cellular responses to local mechanical stress in acute lung injury Am J Physiol Lung Cell Mol Physiol, November 1, 2006; 291(5): L851 - L861. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. M. Li and R. R. Klevecz From the Cover: A rapid genome-scale response of the transcriptional oscillator to perturbation reveals a period-doubling path to phenotypic change PNAS, October 31, 2006; 103(44): 16254 - 16259. [Abstract] [Full Text] [PDF] |
||||
![]() |
Y. Pawitan, S. Michiels, S. Koscielny, A. Gusnanto, and A. Ploner False discovery rate, sensitivity and sample size for microarray studies Bioinformatics, July 1, 2005; 21(13): 3017 - 3024. [Abstract] [Full Text] [PDF] |
||||
![]() |
K. K. Dobbin, E. S. Kawasaki, D. W. Petersen, and R. M. Simon Characterizing dye bias in microarray experiments Bioinformatics, May 15, 2005; 21(10): 2430 - 2437. [Abstract] [Full Text] [PDF] |
||||








