dc.contributor.author | Ruark, E | |
dc.contributor.author | Münz, M | |
dc.contributor.author | Clarke, M | |
dc.contributor.author | Renwick, A | |
dc.contributor.author | Ramsay, E | |
dc.contributor.author | Elliott, A | |
dc.contributor.author | Seal, S | |
dc.contributor.author | Lunter, G | |
dc.contributor.author | Rahman, N | |
dc.date.accessioned | 2017-11-01T12:16:34Z | |
dc.date.issued | 2016-08-03 | |
dc.identifier.citation | Scientific reports, 2016, 6 pp. 31029 - ? | |
dc.identifier.issn | 2045-2322 | |
dc.identifier.uri | https://repository.icr.ac.uk/handle/internal/886 | |
dc.identifier.eissn | 2045-2322 | |
dc.identifier.doi | 10.1038/srep31029 | |
dc.description.abstract | We 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.format | Electronic | |
dc.format.extent | 31029 - ? | |
dc.language | eng | |
dc.language.iso | eng | |
dc.publisher | NATURE PORTFOLIO | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | |
dc.title | OpEx - a validated, automated pipeline optimised for clinical exome sequence analysis. | |
dc.type | Journal Article | |
dcterms.dateAccepted | 2016-07-12 | |
rioxxterms.versionofrecord | 10.1038/srep31029 | |
rioxxterms.licenseref.uri | https://creativecommons.org/licenses/by/4.0 | |
rioxxterms.licenseref.startdate | 2016-08-03 | |
rioxxterms.type | Journal Article/Review | |
dc.relation.isPartOf | Scientific reports | |
pubs.notes | No 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-status | Published | |
pubs.volume | 6 | |
pubs.embargo.terms | No embargo | |
icr.researchteam | Genetic Susceptibility | |
dc.contributor.icrauthor | Clarke, Matthew | |