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Bioinformatics Advance Access published online on January 24, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl004
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received June 16, 2005
Revised December 28, 2005
Accepted January 13, 2006

Article

Computation of recurrent minimal genomic alterations from array-CGH data

C. Rouveirol 1 *, N. Stransky 2, Ph. Hupé 3, Ph. La Rosa 4, E. Viara 4, E. Barillot 4, and F. Radvanyi 2

1 LRI, UMR CNRS 8623, Université Paris Sud, bât 490 91405 Orsay cedex France
2 UMR CNRS 144, Institut Curie, 26 rue d'Ulm 75248 Paris cedex 05 France
3 UMR CNRS 144, Institut Curie, 26 rue d'Ulm 75248 Paris cedex 05 France; Service de Bioinformatique, Institut Curie, 26 rue d'Ulm 75248 Paris cedex 05 France
4 Service de Bioinformatique, Institut Curie, 26 rue d'Ulm 75248 Paris cedex 05 France

* To whom correspondence should be addressed.
C. Rouveirol, E-mail: celine{at}lri.fr


  Abstract

Motivation: The identification of recurrent genomic alterations can provide insight into the initiation and progression of genetic diseases, such as cancer. Array-CGH can identify chromosomal regions that have been gained or lost, with a resolution of about one megabase, for the cutting-edge techniques. The extraction of discrete profiles from raw array-CGH data has been studied extensively, but subsequent steps in the analysis require flexible, efficient algorithms, particularly if the number of available profiles exceeds a few tens or the number of array probes exceeds a few thousands.

Results: We propose two algorithms for computing minimal and minimal constrained regions of gain and loss from discretised CGH profiles. The second of these algorithms can handle additional constraints describing relevant regions of copy number change. We have validated these algorithms on two public array-CGH datasets.

Availability: From the authors, upon request.

Associate Editor: Martin Bishop
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