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A Bayes Regression Approach to Array-CGH Data (2006)

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.

Publication details
Download http://www.bepress.com/sagmb/vol5/iss1/art3
Publisher The Berkeley Electronic Press
Repository eScholarship@Amherst (United States)
Keywords change point problem, comparative genomic hybridization, DNA copy number imbalance, Computational Biology/Bioinformatics, Microarrays
Type text