1 172

Cited 5 times in

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.
Full Text
Appears in Collections:
1. Journal Papers (연구논문) > 5. Research Institutes (연구소) > Oral Cancer Research Institute (구강종양연구소)
1. Journal Papers (연구논문) > 1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실)
Yonsei Authors
김기열(Kim, Ki Yeol) ORCID logo https://orcid.org/0000-0001-5357-1067
라선영(Rha, Sun Young) ORCID logo https://orcid.org/0000-0002-2512-4531
정현철(Chung, Hyun Cheol) ORCID logo https://orcid.org/0000-0002-0920-9471
RIS (EndNote)
XLS (Excel)
사서에게 알리기


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.