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dc.contributor.authorRuark, E
dc.contributor.authorMünz, M
dc.contributor.authorClarke, M
dc.contributor.authorRenwick, A
dc.contributor.authorRamsay, E
dc.contributor.authorElliott, A
dc.contributor.authorSeal, S
dc.contributor.authorLunter, G
dc.contributor.authorRahman, N
dc.date.accessioned2017-11-01T12:16:34Z
dc.date.issued2016-08-03
dc.identifier.citationScientific reports, 2016, 6 pp. 31029 - ?
dc.identifier.issn2045-2322
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/886
dc.identifier.eissn2045-2322
dc.identifier.doi10.1038/srep31029
dc.description.abstractWe present an easy-to-use, open-source Optimised Exome analysis tool, OpEx (http://icr.ac.uk/opex) that accurately detects small-scale variation, including indels, to clinical standards. We evaluated OpEx performance with an experimentally validated dataset (the ICR142 NGS validation series), a large 1000 exome dataset (the ICR1000 UK exome series), and a clinical proband-parent trio dataset. The performance of OpEx for high-quality base substitutions and short indels in both small and large datasets is excellent, with overall sensitivity of 95%, specificity of 97% and low false detection rate (FDR) of 3%. Depending on the individual performance requirements the OpEx output allows one to optimise the inevitable trade-offs between sensitivity and specificity. For example, in the clinical setting one could permit a higher FDR and lower specificity to maximise sensitivity. In contexts where experimental validation is not possible, minimising the FDR and improving specificity may be a preferable trade-off for slightly lower sensitivity. OpEx is simple to install and use; the whole pipeline is run from a single command. OpEx is therefore well suited to the increasing research and clinical laboratories undertaking exome sequencing, particularly those without in-house dedicated bioinformatics expertise.
dc.formatElectronic
dc.format.extent31029 - ?
dc.languageeng
dc.language.isoeng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titleOpEx - a validated, automated pipeline optimised for clinical exome sequence analysis.
dc.typeJournal Article
dcterms.dateAccepted2016-07-12
rioxxterms.versionofrecord10.1038/srep31029
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2016-08-03
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfScientific reports
pubs.notesNo embargo
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.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
pubs.volume6
pubs.embargo.termsNo embargo
icr.researchteamGenetic Susceptibilityen_US
dc.contributor.icrauthorRahman, Saberaen


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