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Open Access Method

Genome Alteration Print (GAP): a tool to visualize and mine complex cancer genomic profiles obtained by SNP arrays

Tatiana Popova12*, Elodie Manié12, Dominique Stoppa-Lyonnet1234, Guillem Rigaill56, Emmanuel Barillot178 and Marc Henri Stern12

Author Affiliations

1 Centre de Recherche, Institut Curie, 26 rue d'Ulm, Paris, 75248, France

2 INSERM U830, Institut Curie, 26 rue d'Ulm, Paris, 75248, France

3 Department of Tumor Biology, Institut Curie, 26 rue d'Ulm, Paris, 75248, France

4 University Paris Descartes, 12 rue de l'Ecole de Médecine, Paris, 75270, France

5 Translational Research Department, Institut Curie, 1 avenue Claude Vellefaux, Paris, 75475, France

6 MIA 518, AgroParisTech/INRA, 16 rue Claude Bernard, Paris, 75231, France

7 INSERM U900, Institut Curie, 26 rue d'Ulm, Paris, 75248, France

8 Ecole des Mines ParisTech, 35 rue Saint Honoré, Fontainebleau, 77305, France

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Genome Biology 2009, 10:R128  doi:10.1186/gb-2009-10-11-r128

Published: 11 November 2009

Abstract

We describe a method for automatic detection of absolute segmental copy numbers and genotype status in complex cancer genome profiles measured with single-nucleotide polymorphism (SNP) arrays. The method is based on pattern recognition of segmented and smoothed copy number and allelic imbalance profiles. Assignments were verified by DNA indexes of primary tumors and karyotypes of cell lines. The method performs well even for poor-quality data, low tumor content, and highly rearranged tumor genomes.