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Effect of Normalization on Detection of Differentially-Expressed Genes with Moderate Effects  

Cho, Seo-Ae (Interdisciplinary Program in Bioinformatics, Seoul National University)
Lee, Eun-Jee (Interdisciplinary Program in Bioinformatics, Seoul National University)
Kim, Young-Chul (Department of Statistics, Seoul National University)
Park, Tae-Sung (Department of Statistics, Seoul National University)
Publication Information
Genomics & Informatics / v.5, no.3, 2007 , pp. 118-123 More about this Journal
Abstract
The current existing literature offers little guidance on how to decide which method to use to analyze one-channel microarray measurements when dealing with large, grouped samples. Most previous methods have focused on two-channel data;therefore they can not be easily applied to one-channel microarray data. Thus, a more reliable method is required to determine an appropriate combination of individual basic processing steps for a given dataset in order to improve the validity of one-channel expression data analysis. We address key issues in evaluating the effectiveness of basic statistical processing steps of microarray data that can affect the final outcome of gene expression analysis without focusingon the intrinsic data underlying biological interpretation.
Keywords
Normalization; CFS disease; Microarray; ANOVA;
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