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Bioinformatics Advance Access originally published online on January 24, 2006
Bioinformatics 2006 22(7):849-856; 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

Computation of recurrent minimal genomic alterations from array-CGH data

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

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

*To whom correspondence should be addressed.

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 ~1 mb, 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 discretized 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.

Contact: celine{at}lri.fr

Supplementary information: Supplementary data are available at Bioinformatics online.

Received on June 16, 2005; revised on December 28, 2005; accepted on January 13, 2006

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