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A weighted sample size for microarray datasets that considers the variability of variance and multiplicity.

 Ki-Yeol Kim  ;  Hyun Cheol Chung  ;  Sun Young Rha 
 Journal of Bioscience and Bioengineering, Vol.108(3) : 252-258, 2009 
Journal Title
 Journal of Bioscience and Bioengineering 
Issue Date
Microarray experiments are often performed to detect differently expressed genes among different clinical phenotypes. The method used to calculate the appropriate sample size for this purpose differs from the sample size calculation used for general clinical experiments, because microarrays include tens of thousands of genes. We proposed a sample size calculation method that considers variance among an entire gene set and used the Bonferroni correction to address the multiplicity problem. Specifically, by adjusting for the multiplicity problem, the existing equation for sample size calculation was modified based on the Bonferroni correction. By k-means cluster analysis, the variances across all genes can be divided into several groups with similar values, and the sample sizes for each group were subsequently calculated and weight-averaged. The results of this study show that the sample size was related to the number of genes on a chip. The weighted sample size, calculated by the proposed method, preserved the Type I error for selection of significant genes within a microarray data set.
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5. Research Institutes (연구소) > Oral Cancer Research Institute (구강종양연구소) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
Yonsei Authors
Kim, Ki Yeol(김기열) ORCID logo https://orcid.org/0000-0001-5357-1067
Rha, Sun Young(라선영) ORCID logo https://orcid.org/0000-0002-2512-4531
Chung, Hyun Cheol(정현철) ORCID logo https://orcid.org/0000-0002-0920-9471
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