4.4 Article

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

Journal

GENOME BIOLOGY
Volume 16, Issue -, Pages -

Publisher

BMC
DOI: 10.1186/s13059-015-0617-1

Keywords

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Funding

  1. Dutch Cancer Society (KWF) long-term fellowship
  2. KWF grant
  3. ERC Synergy Project CombatCancer
  4. Queen Wilhelmina Award grant from the Dutch Cancer Society (KWF Kankerbestrijding)
  5. Cancer Research UK [13031] Funding Source: researchfish

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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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