A bayes regression approach to array-CGH data

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

doi:10.2202/1544-6115.1149

A bayes regression approach to array-CGH data

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

Department of Biomedical Sciences and Engineering

Research output: Contribution to journal › Review article › peer-review

8 Scopus citations

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.

Original language	English
Pages (from-to)	i-20
Journal	Statistical Applications in Genetics and Molecular Biology
Volume	5
Issue number	1
DOIs	https://doi.org/10.2202/1544-6115.1149
State	Published - 2006

Keywords

Change point problem
Comparative genomic hybridization
DNA copy number imbalance

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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.",

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AU - Wen, Chi Chung

AU - Wu, Yuh Jenn

AU - Huang, Yung Hsiang

AU - Chen, Wei Chen

AU - Liu, Shu Chen

AU - Jiang, Sheng Shih

AU - Juang, Jyh Lyh

AU - Lin, Chung Yen

AU - Fang, Wen Tsen

AU - Chao, Agnes Hsiung

AU - Chang, I. Shou

PY - 2006

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N2 - 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.

AB - 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.

KW - Change point problem

KW - Comparative genomic hybridization

KW - DNA copy number imbalance

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JO - Statistical Applications in Genetics and Molecular Biology

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A bayes regression approach to array-CGH data

Abstract

Keywords

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