BMC Genomics (Nov 2012)

<it>Copynumber:</it> Efficient algorithms for single- and multi-track copy number segmentation

  • Nilsen Gro,
  • Liestøl Knut,
  • Loo Peter Van,
  • Moen Vollan Hans Kristian,
  • Eide Marianne B,
  • Rueda Oscar M,
  • Chin Suet-Feung,
  • Russell Roslin,
  • Baumbusch Lars O,
  • Caldas Carlos,
  • Børresen-Dale Anne-Lise,
  • Lingjærde Ole Christian

DOI
https://doi.org/10.1186/1471-2164-13-591
Journal volume & issue
Vol. 13, no. 1
p. 591

Abstract

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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.

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