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Annual International Conference on Research in Computational Molecular Biology

RECOMB 2007: Research in Computational Molecular Biology pp 122–136Cite as

Framework for Identifying Common Aberrations in DNA Copy Number Data

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 4453))

Abstract

High-resolution array comparative genomic hybridization(aCGH) provides exon-level mapping of DNA aberrations in cells or tissues. Such aberrations are central to carcinogenesis and, in many cases, central to targeted therapy of the cancers. Some of the aberrations are sporadic, one-of-a-kind changes in particular tumor samples; others occur frequently and reflect common themes in cancer biology that have interpretable, causal ramifications. Hence, the difficult task of identifying and mapping common, overlapping genomic aberrations (including amplifications and deletions) across a sample set is an important one; it can provide insight for the discovery of oncogenes, tumor suppressors, and the mechanisms by which they drive cancer development.

In this paper we present an efficient computational framework for identification and statistical characterization of genomic aberrations that are common to multiple cancer samples in a CGH data set. We present and compare three different algorithmic approaches within the context of that framework. Finally, we apply our methods to two datasets – a collection of 20 breast cancer samples and a panel of 60 diverse human tumor cell lines (the NCI-60). Those analyses identified both known and novel common aberrations containing cancer-related genes. The potential impact of the analytical methods is well demonstrated by new insights into the patterns of deletion of CDKN2A (p16), a tumor suppressor gene crucial for the genesis of many types of cancer.

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Author information

Authors and Affiliations

  1. Agilent Laboratories, Santa-Clara, CA,  

    Amir Ben-Dor, Anya Tsalenko, Michael T. Barrett & Zohar Yakhini

  2. Computer Science Dept., Technion, Haifa,  

    Doron Lipson & Zohar Yakhini

  3. National Cancer Institute, Bethesda, MD,  

    Mark Reimers & John N. Weinstein

  4. Department of Genetics, Institute for Cancer Research, Rikshospitalet-Radiumhospitalet Medical Center,  

    Lars O. Baumbusch & Anne-Lise Børresen-Dale

  5. Translational Genomics Research Institute, Phoenix, AZ,  

    Michael T. Barrett

Authors
  1. Amir Ben-Dor
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  2. Doron Lipson
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  3. Anya Tsalenko
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  4. Mark Reimers
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  5. Lars O. Baumbusch
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  6. Michael T. Barrett
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  7. John N. Weinstein
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  8. Anne-Lise Børresen-Dale
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  9. Zohar Yakhini
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Terry Speed Haiyan Huang

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© 2007 Springer Berlin Heidelberg

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Ben-Dor, A. et al. (2007). Framework for Identifying Common Aberrations in DNA Copy Number Data. In: Speed, T., Huang, H. (eds) Research in Computational Molecular Biology. RECOMB 2007. Lecture Notes in Computer Science(), vol 4453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71681-5_9

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  • DOI: https://doi.org/10.1007/978-3-540-71681-5_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71680-8

  • Online ISBN: 978-3-540-71681-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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