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J Bioinform Comput Biol. 2015 Oct;13(5):1550027. doi: 10.1142/S0219720015500274. Epub 2015 Sep 4.

CoNCoS: copy number estimation in cancer with controlled support.

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Cluster of Excellence on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Joseph-Stelzmann-Str. 26, 50931 Cologne, Germany.
Cologne Center for Genomics, University of Cologne, Weyertal 115b, 50931 Cologne, Germany.
Department of Pediatric Oncology and Hematology, University Hospital of Cologne, Kerpener Str. 62, 50931 Cologne, Germany.
Center for Molecular Medicine Cologne, University of Cologne, Robert-Koch-Str. 21, 50931 Cologne, Germany.


Somatic copy number (CN) alterations are major drivers of tumorigenesis and growth. Although next-generation sequencing (NGS) technologies enable a deep genomic analysis of cancers, the analysis of the data remains subject to biases and multiple sources of error, including varying local read coverage. The currently existing algorithms for NGS-based detection of CN abberations do not incorporate information on the local coverage quality. We have developed a new algorithm, copy number estimation with controlled support (CoNCoS) that increases the accuracy of CN estimation in paired tumor/normal exome sequencing data sets by assessing and optimizing the support for a site-specific CN estimate. We show by simulations and in a benchmarking study against single nucleotide polymorphism (SNP) microarray data that our approach outperforms the commonly used methods CNAnorm and VarScan2. Our algorithm is suitable to increase the accuracy of somatic CN analysis by a support-optimized estimation approach.


Cancer; copy number abberations; next-generation sequencing; optimization

[Indexed for MEDLINE]

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