A Bayes Regression Approach to Array-CGH Data

Chi-Chung Wen; Yuh-Jenn Wu; Yung-Hsiang Huang; Wei-Chen Chen; Shu-Chen Liu; Shih Sheng Jiang; Jyh-Lyh Juang; Chung-Yen Lin; Wen-Tsen Fang; Chao Agnes Hsiung; I-Shou Chang

doi:10.2202/1544-6115.1149

Published by De Gruyter February 16, 2006

A Bayes Regression Approach to Array-CGH Data

Chi-Chung Wen , Yuh-Jenn Wu , Yung-Hsiang Huang , Wei-Chen Chen , Shu-Chen Liu , Shih Sheng Jiang , Jyh-Lyh Juang , Chung-Yen Lin , Wen-Tsen Fang , Chao Agnes Hsiung and I-Shou Chang

From the journal Statistical Applications in Genetics and Molecular Biology

https://doi.org/10.2202/1544-6115.1149

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This paper develops a Bayes regression model having change points for the analysis of array-CGH data by utilizing not only the underlying spatial structure of the genomic alterations but also the observation that the noise associated with the ratio of the fluorescence intensities is bigger when the intensities get smaller. We show that this Bayes regression approach is particularly suitable for the analysis of cDNA microarray-CGH data, which are generally noisier than those using genomic clones. A simulation study and a real data analysis are included to illustrate this approach.

Keywords: change point problem; comparative genomic hybridization; DNA copy number imbalance

Published Online: 2006-2-16

A Bayes Regression Approach to Array-CGH Data

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