Open Access Method

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

Tatiana Popova1,2*, Elodie Manié1,2, Dominique Stoppa-Lyonnet1,2,3,4, Guillem Rigaill5,6, Emmanuel Barillot1,7,8 and Marc H Stern1,2

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.