Annals of Epidemiology
Volume 20, Issue 10 , Pages 766-771, October 2010

Detecting Differentially Expressed Genes: Minimizing Burden of Testing and Maximizing Number of Discoveries

  • Wen-Chung Lee, MD, PhD

      Affiliations

    • Corresponding Author InformationAddress correspondence to: Wen-Chung Lee, MD, PhD, Rm. 536, No. 17, Xuzhou Rd., Taipei 100, Taiwan. Fax: 886-2-23511955.

Research Center for Genes, Environment and Human Health and Graduate Institute of Epidemiology, College of Public Health, National Taiwan University, Taipei, Taiwan

Received 6 April 2009; accepted 5 April 2010. published online 28 June 2010.

Purpose

Recent progress in DNA microarray technologies allows researchers to perform genome-wide screening to detect differentially expressed genes. Under the paradigm of false discovery rate control, this paper presents sample size methods.

Methods

The author considers the following two scenarios: 1) planning the sample size to keep the ‘burden of testing’ (defined as the expected number of genes that have to be tested before a true discovery can be made) below a certain level, and 2) given a fixed amount of budget, balancing the number of subjects to be recruited and the number of genes to be tested to maximize the total number of true discoveries.

Results

The study calculates sample sizes to minimize the burden of testing or to maximize the number of discoveries.

Conclusions

The present approach to sample size calculation bears more direct relevance to gene-discovery studies.

Key Words: False Discovery Rate, Gene Expression, Microarray

Selected Abbreviations and Acronyms: QT-PCR, quantitative polymerase chain reaction, FDR, false discovery rate, PF, power function

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PII: S1047-2797(10)00082-7

doi:10.1016/j.annepidem.2010.04.002

Annals of Epidemiology
Volume 20, Issue 10 , Pages 766-771, October 2010

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