Copy number: Efficient algorithms for single- and multi-track copy number segmentation
Loo, Peter Van
Moen Vollan, Hans Kristian
Eide, Marianne B.
Rueda, Oscar M.
Baumbusch, Lars O.
Lingjærde, Ole Christian
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Nilsen, G., Liestøl, K., Loo, P. V., Moen Vollan, H. K., Eide, M. B., Rueda, O. M., Chin, S., et al. (2012). Copy number: Efficient algorithms for single- and multi-track copy number segmentation. https://doi.org/10.1186/1471-2164-13-591
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Abstract Background Cancer progression is associated with genomic instability and an accumulation of gains and losses of DNA. The growing variety of tools for measuring genomic copy numbers, including various types of array-CGH, SNP arrays and high-throughput sequencing, calls for a coherent framework offering unified and consistent handling of single- and multi-track segmentation problems. In addition, there is a demand for highly computationally efficient segmentation algorithms, due to the emergence of very high density scans of copy number. Results A comprehensive Bioconductor package for copy number analysis is presented. The package offers a unified framework for single sample, multi-sample and multi-track segmentation and is based on statistically sound penalized least squares principles. Conditional on the number of breakpoints, the estimates are optimal in the least squares sense. A novel and computationally highly efficient algorithm is proposed that utilizes vector-based operations in R. Three case studies are presented. Conclusions The R package copynumber is a software suite for segmentation of single- and multi-track copy number data using algorithms based on coherent least squares principles.
External DOI: https://doi.org/10.1186/1471-2164-13-591
This record's URL: http://www.dspace.cam.ac.uk/handle/1810/244269
Rights Holder: Gro Nilsen et al.; licensee BioMed Central Ltd.