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dc.contributor.authorMahamdallie, Sen_US
dc.contributor.authorRuark, Een_US
dc.contributor.authorHolt, Een_US
dc.contributor.authorPoyastro-Pearson, Een_US
dc.contributor.authorRenwick, Aen_US
dc.contributor.authorStrydom, Aen_US
dc.contributor.authorSeal, Sen_US
dc.contributor.authorRahman, Nen_US
dc.coverage.spatialEnglanden_US
dc.date.accessioned2019-03-04T14:44:49Z
dc.date.issued2018en_US
dc.identifierhttps://www.ncbi.nlm.nih.gov/pubmed/30175241en_US
dc.identifier.citationWellcome Open Res, 2018, 3 pp. 68 - ?en_US
dc.identifier.issn2398-502Xen_US
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/3118
dc.identifier.doi10.12688/wellcomeopenres.14594.1en_US
dc.description.abstractThe analytical sensitivity of a next generation sequencing (NGS) test reflects the ability of the test to detect real sequence variation. The evaluation of analytical sensitivity relies on the availability of gold-standard, validated, benchmarking datasets. For NGS analysis the availability of suitable datasets has been limited. Most laboratories undertake small scale evaluations using in-house data, and/or rely on in silico generated datasets to evaluate the performance of NGS variant detection pipelines. Cancer predisposition genes (CPGs), such as BRCA1 and BRCA2, are amongst the most widely tested genes in clinical practice today. Hundreds of providers across the world are now offering CPG testing using NGS methods. Validating and comparing the analytical sensitivity of CPG tests has proved difficult, due to the absence of comprehensive, orthogonally validated, benchmarking datasets of CPG pathogenic variants. To address this we present the ICR639 CPG NGS validation series. This dataset comprises data from 639 individuals. Each individual has sequencing data generated using the TruSight Cancer Panel (TSCP), a targeted NGS assay for the analysis of CPGs, together with orthogonally generated data showing the presence of at least one CPG pathogenic variant per individual. The set consists of 645 pathogenic variants in total. There is strong representation of the most challenging types of variants to detect, with 339 indels, including 16 complex indels and 24 with length greater than five base pairs and 74 exon copy number variations (CNVs) including 23 single exon CNVs. The series includes pathogenic variants in 31 CPGs, including 502 pathogenic variants in BRCA1 or BRCA2, making this an important comprehensive validation dataset for providers of BRCA1 and BRCA2 NGS testing. We have deposited the TSCP FASTQ files of the ICR639 series in the European Genome-phenome Archive (EGA) under accession number EGAD00001004134.en_US
dc.format.extent68 - ?en_US
dc.languageengen_US
dc.language.isoengen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectBRCA1 and BRCA2en_US
dc.subjectanalytical sensitivityen_US
dc.subjectcancer predisposition geneen_US
dc.subjectgenetic testingen_US
dc.subjectnext generation sequencingen_US
dc.subjectvalidationen_US
dc.subjectvariant benchmarkingen_US
dc.titleThe ICR639 CPG NGS validation series: A resource to assess analytical sensitivity of cancer predisposition gene testing.en_US
dc.typeJournal Article
dcterms.dateAccepted2018-06-06en_US
rioxxterms.versionofrecord10.12688/wellcomeopenres.14594.1en_US
rioxxterms.licenseref.startdate2018en_US
rioxxterms.typeJournal Article/Reviewen_US
dc.relation.isPartOfWellcome Open Resen_US
pubs.notesNot knownen_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.volume3en_US
pubs.embargo.termsNot knownen_US
icr.researchteamGenetic Susceptibilityen_US
dc.contributor.icrauthorRahman, Saberaen_US


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