A robust two-way semi-linear model for normalization of cDNA microarray data

Background: Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative expression values. Methods: We propose a robust semiparametric method in a two-way semi-linear model (TWSLM) for normalization of cDNA microarray data. This method does not make the usual assumptions underlying some of the existing methods. For example, it does not assume that: (i) the percentage of differentially expressed genes is small; or (ii) the numbers of up- and down-regulated genes are about the same, as required in the LOWESS normalization method. We conduct simulation studies to evaluate the proposed method and use a real data set from a specially designed microarray experiment to compare the performance of the proposed method with that of the LOWESS normalization approach. Results: The simulation results show that the proposed method performs better than the LOWESS normalization method in terms of ...

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Deli Wang, Jian Huang, Hehuang Xie, Liliana Manzella, Marcelo Bento Soares
• Keywords: BMCBI 2005, LOWESS Normalization Method, Microarray Data, Real Data