Framework for identifying common aberrations in DNA copy number data

Amir Ben-Dor, Doron Lipson, Anya Tsalenko, Mark Reimers, Lars O. Baumbusch, Michael T. Barrett, John N. Weinstein, Anne Lise Børresen-Dale, Zohar Yakhini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationResearch in Computational Molecular Biology - 11th Annual International Conference, RECOMB 2007, Proceedings
PublisherSpringer Verlag
Number of pages15
ISBN (Print)3540716807, 9783540716808
StatePublished - 2007
Event11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007 - Oakland, CA, United States
Duration: Apr 21 2007Apr 25 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4453 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007
Country/TerritoryUnited States
CityOakland, CA


  • Breast cancer
  • CGH
  • Cancer
  • Common aberrations
  • Microarray data analysis
  • NCI-60

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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