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Bioinformatics Advance Access published online on July 20, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm364
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Analysis of Array CGH Data for Cancer Studies Using Fused Quantile Regression

Youjuan Li and Ji Zhu *

Department of Statistics, University of Michigan

*To whom correspondence should be addressed. Prof. Ji Zhu, E-mail: jizhu{at}umich.edu


  Abstract

Motivation: The identification of DNA copy number changes provides insights that may advance our understanding of initiation and progression of cancer. Array-based comparative genomic hybridization (array-CGH) has emerged as a technique allowing high throughput genome-wide scanning for chromosomal aberrations. A number of statistical methods have been proposed for the analysis of array-CGH data. In this paper, we consider a fused quantile regression model based on three motivations: 1) quantile regression may provide a more comprehensive picture for the ratio profile of copy numbers than the standard mean regression approach; 2) for simplicity, most available methods assume uniform spacing between neighboring clones, while incorporating the information of physical locations of clones may be helpful; 3) most current methods have a set of tuning parameters that must be carefully tuned, which introduces complexity to the implementation.

Results: We formulate the detection of regions of gains and losses in a fused regularized quantile regression framework, incorporating physical locations of clones. We derive an efficient algorithm that computes the entire solution path for the resulting optimization problem, and we propose a simple estimate for the complexity of the fitted model, which leads to convenient selection of the tuning parameter. Three published array-CGH datasets are used to demonstrate our approach.

Availability: R code are available at http://www.stat.lsa.umich.edu/~jizhu/code/cgh/.

Associate Editor: Dr. Jonathan Wren

Received on March 25, 2007; revised on June 12, 2007; accepted on July 8, 2007

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