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The normalization method for cDNA microarray data

Published online by Cambridge University Press:  20 March 2007

Zhang Ji-Gang ,
Zhang Qin  and
Yin Zong-Jun
Zhang Ji-Gang
Affiliation:
China Agricultural University, College of Animal Science and Technology, Beijing 100094, China
Zhang Qin*
Affiliation:
China Agricultural University, College of Animal Science and Technology, Beijing 100094, China
Yin Zong-Jun
Affiliation:
China Agricultural University, College of Animal Science and Technology, Beijing 100094, China
*
*Corresponding author. E-mail: qzhang@cau.edu.cn
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Abstract

The widely used processing method for cDNA microarray data involves background correction, log-ratio transformation and data normalization before the statistical testing can be done. Here we propose a method that avoids the log-transformation step in view of its drawbacks, but goes directly to normalization after background correction. This method could better estimate the ‘noise’ effect by utilizing the information more effectively. Simulation studies were carried out to compare the feasibility and efficiency of this approach for eliminating experimental ‘noise’ with the log-ratio approach. Results showed that our approach worked well and the method was more robust and powerful than the log-ratio approach.

Keywords

cDNA microarraylog-rationon-transformationnormalization
Type
Research Article
Information
Chinese Journal of Agricultural Biotechnology , Volume 3 , Issue 3 , December 2006 , pp. 195 - 199
Copyright
China Agricultural University and Cambridge University Press 2006

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References

Chen, Y, Dougherty, ER and Bittner, ML (1997) Ratio–based decisions and the quantitative analysis of cDNA microarray images. Journal of Biomedical Optics 2(4): 364–374.CrossRefGoogle ScholarPubMed
Cui, XQ and Churchill, GA (2003) Statistical tests for differential expression in cDNA microarray experiments. Genome Biology 4(4): 210.1–210.10.Google Scholar
Cui, XQ, Kerr, MK and Churchill, GA (2003) Transformations for cDNA microarray data. Statistical Applications in Genetics and Molecular Biology 2(1): article 4.Google Scholar
Derisi, J, Iyer, V and Brown, P (1997) Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 278: 680–686.Google Scholar
Eisen, MB, Spellman, PT, Brown, PO and Botstein, D (1998) Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Sciences of the United States of America 95: 14863–14868.Google Scholar
Futschik, M and Crompton, T (2004) Model selection and efficiency testing for normalization of cDNA microarray data. Genome Biology 5(8): R60.Google Scholar
Ge, YC, Dudoit, S and Speed, TP (2003) Resampling-based multiple testing for microarray data analysis. TEST 12, 1–44.Google Scholar
Huber, W, von Heydebreck, A, Sültmann, H, Poustka, A and Vingron, M (2003) Parameter estimation for the calibration and variance stabilization of microarray data. Statistical Applications in Genetics and Molecular Biology 2(1): 3.CrossRefGoogle ScholarPubMed
Newton, MA, Kendziorski, CM, Richmond, CS, Blattner, FR and Tsui, KW (2001) On differential variablility of expression ratios: improving statistical inference about gene expression changes from microarray data. Journal of Computational Biology 8: 37–52.Google Scholar
Reiner, A, Yekutieli, D and Benjamini, Y (2003) Identifying differentially expressed genes using false discovery rate controlling procedures. Bioinformatics 19(3): 368–375.CrossRefGoogle ScholarPubMed
Rocke, DM and Durbin, B (2001) A model for measurement error for gene expression arrays. Journal of Computational Biology 8: 557–569.Google Scholar
Yang, YH, Buckley, MJ, Dudoit, S and Speed, TP (2001) Comparison of methods for image analysis on cDNA microarray. Journal of Computational and Graphical Statistics 11: 108–136.Google Scholar
Yang, YH, Dudoit, S, Luu, P, Lin, DM, Peng, V, Ngai, J and Speed, TP (2002) Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Research 30(4): e15.CrossRefGoogle Scholar