%0 Journal Article %1 Kuilman2015 %A Kuilman, Thomas %A Velds, Arno %A Kemper, Kristel %A Ranzani, Marco %A Bombardelli, Lorenzo %A Hoogstraat, Marlous %A Nevedomskaya, Ekaterina %A Xu, Guotai %A de Ruiter, Julian %A Lolkema, Martijn P. %A Ylstra, Bauke %A Jonkers, Jos %A Rottenberg, Sven %A Wessels, Lodewyk F. %A Adams, David J. %A Peeper, Daniel S. %A Krijgsman, Oscar %D 2015 %J Genome Biology %K cancer-research fulltext ngs software structural-variation %N 1 %P 49 %R 10.1186/s13059-015-0617-1 %T CopywriteR: DNA copy number detection from off-target sequence data %U https://doi.org/10.1186/s13059-015-0617-1 %V 16 %X 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.

@article{Kuilman2015, abstract = {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.}, added-at = {2021-02-28T15:05:12.000+0100}, author = {Kuilman, Thomas and Velds, Arno and Kemper, Kristel and Ranzani, Marco and Bombardelli, Lorenzo and Hoogstraat, Marlous and Nevedomskaya, Ekaterina and Xu, Guotai and de Ruiter, Julian and Lolkema, Martijn P. and Ylstra, Bauke and Jonkers, Jos and Rottenberg, Sven and Wessels, Lodewyk F. and Adams, David J. and Peeper, Daniel S. and Krijgsman, Oscar}, biburl = {https://www.bibsonomy.org/bibtex/267fa9aeeca2b65cfc1ae05bc39c4e472/marcsaric}, day = 27, description = {CopywriteR: DNA copy number detection from off-target sequence data | SpringerLink}, doi = {10.1186/s13059-015-0617-1}, interhash = {daad88979a3cf00d3e9bd0e2568fceae}, intrahash = {67fa9aeeca2b65cfc1ae05bc39c4e472}, issn = {1465-6906}, journal = {Genome Biology}, keywords = {cancer-research fulltext ngs software structural-variation}, month = feb, number = 1, pages = 49, timestamp = {2021-02-28T15:05:12.000+0100}, title = {CopywriteR: DNA copy number detection from off-target sequence data}, url = {https://doi.org/10.1186/s13059-015-0617-1}, volume = 16, year = 2015 }