A Bayes Regression Approach to Array-CGH Data

Abstract 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. Submitted: April 18, 2005 · Accepted: January 13, 2006 · Published: February 16, 2006 Recommended Citation Wen, Chi-Chung; Wu, Yuh-Jenn; Huang, Yung-Hsiang; Chen, Wei-Chen; Liu, Shu-Chen; Jiang, Shih Sheng; Juang, Jyh-Lyh; Lin, Chung-Yen; Fang, Wen-Tsen; Hsiung, Chao Agnes; and Chang, I-Shou (2006) "A Bayes Regression Approach to Array-CGH Data," Statistical Applications in Genetics and Molecular Biology: Vol. 5 : Iss. 1, Article 3. DOI: 10.2202/1544-6115.1149 Available at: http://www.bepress.com/sagmb/vol5/iss1/art3