title: Sequential model selection-based segmentation to detect DNA copy number variation.
abstract: Array-based CGH experiments are designed to detect genomic aberrations or regions of DNA copy-number variation that are associated with an outcome, typically a state of disease. Most of the existing statistical methods target on detecting DNA copy number variations in a single sample or array. We focus on the detection of group effect variation, through simultaneous study of multiple samples from multiple groups. Rather than using direct segmentation or smoothing techniques, as commonly seen in existing detection methods, we develop a sequential model selection procedure that is guided by a modified Bayesian information criterion. This approach improves detection accuracy by accumulatively utilizing information across contiguous clones, and has computational advantage over the existing popular detection methods. Our empirical investigation suggests that the performance of the proposed method is superior to that of the existing detection methods, in particular, in detecting small segments or separating neighboring segments with differential degrees of copy-number variation.
authors.affiliation: Department of Biostatistics, UT M. D. Anderson Cancer Center, Houston, Texas 77030, U.S.A.. jhu@mdanderson.org.
authors.forename: Jianhua
authors.initials: J
authors.lastname: Hu
authors.affiliation: School of Economics, Shanghai University, Shanghai 200444, China. liwenzhang@shu.edu.cn.
authors.forename: Liwen
authors.initials: L
authors.lastname: Zhang
authors.affiliation: Department of Statistics, George Washington University, Washington D.C. 20052, U.S.A.. judywang@gwu.edu.
authors.forename: Huixia Judy
authors.initials: HJ
authors.lastname: Wang
mesh_terms: D001499:Bayes Theorem; D002999:Clone Cells; D055028:Comparative Genomic Hybridization / Q000706:statistics & numerical data*; D056915:DNA Copy Number Variations / Q000235:genetics*; D020022:Genetic Predisposition to Disease; D006801:Humans; D015233:Models, Statistical; D009101:Multiple Myeloma / Q000235:genetics / Q000473:pathology
keywords: Array-based CGH; Bayesian information criterion; Copy-number variation; Segmentation; Sequential model selection