Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

<ns4:p><ns4:bold>Background:</ns4:bold> Targeted next generation sequencing (NGS) panels are increasingly being used in clinical genomics to increase capacity, throughput and affordability of gene testing. Identifying whole exon deletions or duplications (termed exon copy number variants, ‘exon CNVs’) in exon-targeted NGS panels has proved challenging, particularly for single exon CNVs. </ns4:p><ns4:p> <ns4:bold>Methods:</ns4:bold> We developed a tool for the <ns4:underline>D</ns4:underline>etection of <ns4:underline>E</ns4:underline>xon <ns4:underline>Co</ns4:underline>py <ns4:underline>N</ns4:underline>umber variants (DECoN), which is optimised for analysis of exon-targeted NGS panels in clinical settings. We evaluated DECoN performance using 96 samples with independently validated exon CNV data. We performed simulations to evaluate DECoN detection performance of single exon CNVs and evaluate performance using different coverage levels and sample numbers. Finally, we implemented DECoN in a clinical laboratory that tests <ns4:italic>BRCA1</ns4:italic> and <ns4:italic>BRCA2</ns4:italic> with the TruSight Cancer Panel (TSCP). We used DECoN to analyse 1,919 samples, validating exon CNV detections by multiplex ligation-dependent probe amplification (MLPA). </ns4:p><ns4:p> <ns4:bold>Results:</ns4:bold> In the evaluation set, DECoN achieved 100% sensitivity and 99% specificity for BRCA exon CNVs, including identification of 8 single exon CNVs. DECoN also identified 14/15 exon CNVs in 8 other genes. Simulations of all possible BRCA single exon CNVs gave a mean sensitivity of 98% for deletions and 95% for duplications. DECoN performance remained excellent with different levels of coverage and sample numbers; sensitivity and specificity was &gt;98% with the typical NGS run parameters. In the clinical pipeline, DECoN automatically analyses pools of 48 samples at a time, taking 24 minutes per pool, on average. DECoN detected 24 BRCA exon CNVs, of which 23 were confirmed by MLPA, giving a false discovery rate of 4%. Specificity was 99.7%. </ns4:p><ns4:p> <ns4:bold>Conclusions:</ns4:bold> DECoN is a fast, accurate, exon CNV detection tool readily implementable in research and clinical NGS pipelines. It has high sensitivity and specificity and acceptable false discovery rate. DECoN is freely available at <ns4:ext-link xmlns:ns3="http://www.w3.org/1999/xlink" ext-link-type="uri" ns3:href="http://www.icr.ac.uk/decon">www.icr.ac.uk/decon</ns4:ext-link>.</ns4:p>

Original publication

DOI

10.12688/wellcomeopenres.10069.1

Type

Journal article

Journal

Wellcome Open Research

Publisher

F1000 Research Ltd

Publication Date

25/11/2016

Volume

1

Pages

20 - 20