A Linear-Time Algorithm for Analyzing Array CGH Data Using Log Ratio Triangulation
ISBRA '09 Proceedings of the 5th International Symposium on Bioinformatics Research and Applications
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A Bayesian analysis for identifying DNA copy number variations using a compound Poisson process
EURASIP Journal on Bioinformatics and Systems Biology
Detection of chromosomal abnormalities using high resolution arrays in clinical cancer research
Journal of Biomedical Informatics
Computational Statistics & Data Analysis
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Motivation: Array CGH technologies enable the simultaneous measurement of DNA copy number for thousands of sites on a genome. We developed the circular binary segmentation (CBS) algorithm to divide the genome into regions of equal copy number. The algorithm tests for change-points using a maximal t-statistic with a permutation reference distribution to obtain the corresponding P-value. The number of computations required for the maximal test statistic is O(N2), where N is the number of markers. This makes the full permutation approach computationally prohibitive for the newer arrays that contain tens of thousands markers and highlights the need for a faster algorithm. Results: We present a hybrid approach to obtain the P-value of the test statistic in linear time. We also introduce a rule for stopping early when there is strong evidence for the presence of a change. We show through simulations that the hybrid approach provides a substantial gain in speed with only a negligible loss in accuracy and that the stopping rule further increases speed. We also present the analyses of array CGH data from breast cancer cell lines to show the impact of the new approaches on the analysis of real data. Availability: An R version of the CBS algorithm has been implemented in the "DNAcopy" package of the Bioconductor project. The proposed hybrid method for the P-value is available in version 1.2.1 or higher and the stopping rule for declaring a change early is available in version 1.5.1 or higher. Contact: venkatre@mskcc.org Supplementary information: Supplementary data are available at Bioinformatics online.