A comparison study: applying segmentation to array CGH data for downstream analyses.
BACKGROUND
Array comparative genomic hybridization (CGH) allows detection and mapping of copy number of DNA segments. A challenge is to make inferences about the copy number structure of the genome. Several statistical methods have been proposed to determine genomic segments with different copy number levels. However, to date, no comprehensive comparison of various characteristics of these methods exists. Moreover, the segmentation results have not been utilized in downstream analyses.


RESULTS
We describe a comparison of three popular and publicly available methods for the analysis of array CGH data and we demonstrate how segmentation results may be utilized in the downstream analyses such as testing and classification, yielding higher power and prediction accuracy. Since the methods operate on individual chromosomes, we also propose a novel procedure for merging segments across the genome, which results in an interpretable set of copy number levels, and thus facilitate identification of copy number alterations in each genome.


BACKGROUND
http://www.bioconductor.org
Willenbrock
Hanni
H
Center for Biological Sequence Analysis, Department of Biotechnology, Technical University of Denmark, Kgs. Lyngby.
Fridlyand
Jane
J
D000465:Algorithms; D002294:Carcinoma, Squamous Cell / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D004247:DNA / Q000235:genetics; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D015972:Gene Expression Regulation, Neoplastic; D015723:Gene Library; D005821:Genetic Techniques; D016678:Genome; D006801:Humans; D020407:Internet; D009062:Mouth Neoplasms / Q000235:genetics; D009693:Nucleic Acid Hybridization; D017422:Sequence Analysis, DNA; D012984:Software
D004247:DNA