Detection of chromosomal abnormalities using high resolution arrays in clinical cancer research

Authors:
Cyril Dalmasso;Philippe Broët
Affiliations:
Genome Institute of Singapore, 60 Biopolis Street, 02-01 Genome, Singapore and Laboratoire Statistique et Génome, Université d'Evry Val d'Essonne, UMR CNRS 8071- USC INRA, 91000 Evry, Fr ...;Genome Institute of Singapore, 60 Biopolis Street, 02-01 Genome, Singapore and JE 2492, Faculty of Medicine, University of Paris-Sud, Le Kremlin-Bicêtre, France
Venue:
Journal of Biomedical Informatics
Year:
2011

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Abstract

In clinical cancer research, high throughput genomic technologies are increasingly used to identify copy number aberrations. However, the admixture of tumor and stromal cells and the inherent karyotypic heterogeneity of most of the solid tumor samples make this task highly challenging. Here, we propose a robust two-step strategy to detect copy number aberrations in such a context. A spatial mixture model is first used to fit the preprocessed data. Then, a calling algorithm is applied to classify the genomic segments in three biologically meaningful states (copy loss, copy gain and modal copy). The results of a simulation study show the good properties of the proposed procedure with complex patterns of genomic aberrations. The interest of the proposed procedure in clinical cancer research is then illustrated by the analysis of real lung adenocarcinoma samples.