CopywriteR: DNA copy number detection from off-target sequence data

Current methods for detection of copy number variants (CNV) and aberrations (CNA) from targeted sequencing data are based on the depth of coverage of captured exons. Accurate CNA determination is complicated by uneven genomic distribution and non-uniform capture efficiency of targeted exons. Here we...

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Bibliographic Details
Published in:Genome Biology Vol. 16; no. 1; p. 49
Main Authors: Kuilman, Thomas, Velds, Arno, Kemper, Kristel, Ranzani, Marco, Bombardelli, Lorenzo, Hoogstraat, Marlous, Nevedomskaya, Ekaterina, Xu, Guotai, de Ruiter, Julian, Lolkema, Martijn P, Ylstra, Bauke, Jonkers, Jos, Rottenberg, Sven, Wessels, Lodewyk F, Adams, David J, Peeper, Daniel S, Krijgsman, Oscar
Format: Journal Article
Language:English
Published: London BioMed Central 27.02.2015
Springer Nature B.V
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ISSN:1465-6906, 1474-7596, 1465-6906, 1474-760X, 1465-6914
Online Access:Get full text
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Summary:Current methods for detection of copy number variants (CNV) and aberrations (CNA) from targeted sequencing data are based on the depth of coverage of captured exons. Accurate CNA determination is complicated by uneven genomic distribution and non-uniform capture efficiency of targeted exons. Here we present CopywriteR, which eludes these problems by exploiting ‘off-target’ sequence reads. CopywriteR allows for extracting uniformly distributed copy number information, can be used without reference, and can be applied to sequencing data obtained from various techniques including chromatin immunoprecipitation and target enrichment on small gene panels. CopywriteR outperforms existing methods and constitutes a widely applicable alternative to available tools.
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ISSN:1465-6906
1474-7596
1465-6906
1474-760X
1465-6914
DOI:10.1186/s13059-015-0617-1