alexa Sample Size Calculation for Microarray Studies with Sur
ISSN: 0974-7230

Journal of Computer Science & Systems Biology
Open Access

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Research Article

Sample Size Calculation for Microarray Studies with Survival Endpoints

Sin-Ho Jung*

Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA

Samsung Cancer Research Institute, Samsung Medical Center, Seoul, Korea

*Corresponding Author:
Sin-Ho Jung
Department of Biostatistics and Bioinformatics
Duke University, Durham, NC, USA
E-mail: [email protected]

Received date: June 06, 2013; Accepted date: July 19, 2013; Published date: July 26, 2013

Citation: Jung SH (2013) Sample Size Calculation for Microarray Studies with Survival Endpoints. J Comput Sci Syst Biol 6:177-181. doi:10.4172/jcsb.1000114

Copyright: © 2013 Jung SH. This is an open-access article distributed under the terms of the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



Oftentimes, we want to discover the genes whose expression levels are associated with a time-to-event endpoint, such as progression free survival or overall survival, through microarray studies. In this case, we need to adjust the false positivity in such discovery procedure for multiplicity of the genes using a multiple testing method. The most popular multiple testing methods used for gene discovery in microarray studies are to control the false discovery rate or the family wise error rate. In this paper, we review a FDR-control method to discover the genes associated with a time-to-event outcome and propose a sample size calculation method for microarray studies designed to discover genes whose expression levels are associated the chosen time-to-event outcome. These methods can be easily modified for other types of high throughput genome projects.

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