CORE: A Software Tool for Delineating Regions of Recurrent DNA Copy Number Alteration in Cancer

  • Guoli Sun
  • Alexander KrasnitzEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1878)


Collections of genomic intervals are a common data type across many areas of computational biology. In cancer genomics, in particular, the intervals often represent regions with altered DNA copy number, and their collections exhibit recurrent features, characteristic of a given cancer type. Cores of Recurrent Events (CORE) is a versatile computational tool for identification of such recurrent features. Here we provide practical guidance for the use of CORE, implemented as an eponymous R package.

Key words

Somatic copy number alterations Combinatorial optimization R language Parallelization 


  1. 1.
    Beroukhim R, Mermel CH, Porter D, Wei G, Raychaudhuri S, Donovan J, Barretina J, Boehm JS, Dobson J, Urashima M, Mc Henry KT, Pinchback RM, Ligon AH, Cho YJ, Haery L, Greulich H, Reich M, Winckler W, Lawrence MS, Weir BA, Tanaka KE, Chiang DY, Bass AJ, Loo A, Hoffman C, Prensner J, Liefeld T, Gao Q, Yecies D, Signoretti S, Maher E, Kaye FJ, Sasaki H, Tepper JE, Fletcher JA, Tabernero J, Baselga J, Tsao MS, Demichelis F, Rubin MA, Janne PA, Daly MJ, Nucera C, Levine RL, Ebert BL, Gabriel S, Rustgi AK, Antonescu CR, Ladanyi M, Letai A, Garraway LA, Loda M, Beer DG, True LD, Okamoto A, Pomeroy SL, Singer S, Golub TR, Lander ES, Getz G, Sellers WR, Meyerson M (2010) The landscape of somatic copy-number alteration across human cancers. Nature 463(7283):899–905. Scholar
  2. 2.
    Navin N, Kendall J, Troge J, Andrews P, Rodgers L, McIndoo J, Cook K, Stepansky A, Levy D, Esposito D, Muthuswamy L, Krasnitz A, McCombie WR, Hicks J, Wigler M (2011) Tumour evolution inferred by single-cell sequencing. Nature 472(7341):90–94. Scholar
  3. 3.
    Hicks J, Krasnitz A, Lakshmi B, Navin NE, Riggs M, Leibu E, Esposito D, Alexander J, Troge J, Grubor V, Yoon S, Wigler M, Ye K, Borresen-Dale AL, Naume B, Schlicting E, Norton L, Hagerstrom T, Skoog L, Auer G, Maner S, Lundin P, Zetterberg A (2006) Novel patterns of genome rearrangement and their association with survival in breast cancer. Genome Res 16(12):1465–1479. Scholar
  4. 4.
    Krishnamurti U, Silverman JF (2014) HER2 in breast cancer: a review and update. Adv Anat Pathol 21(2):100–107. Scholar
  5. 5.
    Xue W, Kitzing T, Roessler S, Zuber J, Krasnitz A, Schultz N, Revill K, Weissmueller S, Rappaport AR, Simon J, Zhang J, Luo W, Hicks J, Zender L, Wang XW, Powers S, Wigler M, Lowe SW (2012) A cluster of cooperating tumor-suppressor gene candidates in chromosomal deletions. Proc Natl Acad Sci U S A 109(21):8212–8217. Scholar
  6. 6.
    Krasnitz A, Sun G, Andrews P, Wigler M (2013) Target inference from collections of genomic intervals. Proc Natl Acad Sci U S A 110(25):E2271–E2278. Scholar
  7. 7.
    Sun G, Krasnitz A (2014) CORE: cores of recurrent events.
  8. 8.
    Kendall J, Krasnitz A (2014) Computational methods for DNA copy-number analysis of tumors. Methods Mol Biol 1176:243–259. Scholar
  9. 9.
    Bajjani BA, Theisen AP, Ballif BC, Shaffer LG (2005) Array-based comparative genomic hybridization in clinical diagnosis. Expert Rev Mol Diagn 5(3):421–429CrossRefGoogle Scholar
  10. 10.
    Mei R, Galipeau PC, Prass C, Berno A, Ghandour G, Patil N, Wolff RK, Chee MS, Reid BJ, Lockhart DJ (2000) Genome-wide detection of allelic imbalance using human SNPs and high-density DNA arrays. Genome Res 10(8):1126–1137. Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Intuit Inc.Mountain ViewUSA
  2. 2.Simons Center for Quantitative BiologyCold Spring Harbor LaboratoryCold Spring HarborUSA

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