Abstract
Background: 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. Methods: We developed a tool for the Detection of Exon Copy Number variants (DECoN), which is optimised for analysis of exon-targeted NGS panels in the clinical setting. 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 to evaluate performance using different coverage levels and sample numbers. Finally, we implemented DECoN in a clinical laboratory that tests BRCA1 and BRCA2 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). Results: 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 >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%. Conclusions: 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 www.icr.ac.uk/decon.
Highlights
Targeted generation sequencing (NGS) panels are increasingly being used in clinical genomics to increase capacity, throughput and affordability of gene testing[1,2,3]
With extensive real and simulated data we show that Detection of Exon Copy Number variants (DECoN) has high sensitivity and specificity and can be used as the first-line exon Copy number variant (CNV) detection tool in exon-targeted next generation sequencing (NGS) panel analysis
Inspection of the DECoN visualisation showed this was to be expected, as the trace did not show the clear separation from the reference samples observed in true CNVs (Supplementary File 2a)
Summary
Targeted generation sequencing (NGS) panels are increasingly being used in clinical genomics to increase capacity, throughput and affordability of gene testing[1,2,3]. Accurate detection of deletions or duplications of whole exons, known as exon copy number variants (exon CNVs), has proved problematic in targeted NGS data, detection of single exon CNVs7,8 In large part this is because the breakpoints usually lie outside the region targeted by the panel, and detection methods are typically based on changes in the number of reads covering each target, commonly referred to as read depth or coverage. Coverage can vary for several reasons, such as differences in GC content or individual probe efficiencies, and careful normalisation of data is required[7,8] These challenges have led many research and clinical laboratories to either ignore exon CNVs or to use alternative detection methods[9].
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