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dc.contributor.authorFowler, Aen_US
dc.contributor.authorMahamdallie, Sen_US
dc.contributor.authorRuark, Een_US
dc.contributor.authorSeal, Sen_US
dc.contributor.authorRamsay, Een_US
dc.contributor.authorClarke, Men_US
dc.contributor.authorUddin, Ien_US
dc.contributor.authorWylie, Hen_US
dc.contributor.authorStrydom, Aen_US
dc.contributor.authorLunter, Gen_US
dc.contributor.authorRahman, Nen_US
dc.coverage.spatialEnglanden_US
dc.date.accessioned2017-11-01T11:45:18Z
dc.date.issued2016-11-25en_US
dc.identifierhttps://www.ncbi.nlm.nih.gov/pubmed/28459104en_US
dc.identifier.citationWellcome Open Res, 2016, 1 pp. 20 - ?en_US
dc.identifier.issn2398-502Xen_US
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/885
dc.identifier.doi10.12688/wellcomeopenres.10069.1en_US
dc.description.abstractBackground: 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.en_US
dc.format.extent20 - ?en_US
dc.languageengen_US
dc.language.isoengen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectBRCA1en_US
dc.subjectBRCA2en_US
dc.subjectCNVen_US
dc.subjectExon CNVen_US
dc.subjectNGSen_US
dc.subjectclinical genomicsen_US
dc.subjectgenetic testingen_US
dc.subjectmutation testingen_US
dc.titleAccurate clinical detection of exon copy number variants in a targeted NGS panel using DECoN.en_US
dc.typeJournal Article
dcterms.dateAccepted2016-11-25en_US
rioxxterms.versionofrecord10.12688/wellcomeopenres.10069.1en_US
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0en_US
rioxxterms.licenseref.startdate2016-11-25en_US
rioxxterms.typeJournal Article/Reviewen_US
dc.relation.isPartOfWellcome Open Resen_US
pubs.notesNo embargoen_US
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research/Genetic Susceptibility
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Genetic Susceptibility
pubs.publication-statusPublished onlineen_US
pubs.volume1en_US
pubs.embargo.termsNo embargoen_US
icr.researchteamGenetic Susceptibilityen_US
dc.contributor.icrauthorRahman, Saberaen_US
dc.contributor.icrauthorWylie, Harrieten_US


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