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dc.contributor.authorCubuk, C
dc.contributor.authorGarrett, A
dc.contributor.authorChoi, S
dc.contributor.authorKing, L
dc.contributor.authorLoveday, C
dc.contributor.authorTorr, B
dc.contributor.authorBurghel, GJ
dc.contributor.authorDurkie, M
dc.contributor.authorCallaway, A
dc.contributor.authorRobinson, R
dc.contributor.authorDrummond, J
dc.contributor.authorBerry, I
dc.contributor.authorWallace, A
dc.contributor.authorEccles, D
dc.contributor.authorTischkowitz, Marc
dc.contributor.authorWhiffin, N
dc.contributor.authorWare, JS
dc.contributor.authorHanson, H
dc.contributor.authorTurnbull, C
dc.contributor.authorCanVIG-Uk
dc.date.accessioned2021-10-28T15:27:10Z
dc.date.available2021-10-28T15:27:10Z
dc.date.issued2021-11
dc.date.submitted2021-02-02
dc.identifier.issn1098-3600
dc.identifier.others41436-021-01265-z
dc.identifier.other1265
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/330003
dc.description.abstractPURPOSE: Where multiple in silico tools are concordant, the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) framework affords supporting evidence toward pathogenicity or benignity, equivalent to a likelihood ratio of ~2. However, limited availability of "clinical truth sets" and prior use in tool training limits their utility for evaluation of tool performance. METHODS: We created a truth set of 9,436 missense variants classified as deleterious or tolerated in clinically validated high-throughput functional assays for BRCA1, BRCA2, MSH2, PTEN, and TP53 to evaluate predictive performance for 44 recommended/commonly used in silico tools. RESULTS: Over two-thirds of the tool-threshold combinations examined had specificity of <50%, thus substantially overcalling deleteriousness. REVEL scores of 0.8-1.0 had a Positive Likelihood Ratio (PLR) of 6.74 (5.24-8.82) compared to scores <0.7 and scores of 0-0.4 had a Negative Likelihood Ratio (NLR) of 34.3 (31.5-37.3) compared to scores of >0.7. For Meta-SNP, the equivalent PLR = 42.9 (14.4-406) and NLR = 19.4 (15.6-24.9). CONCLUSION: Against these clinically validated "functional truth sets," there was wide variation in the predictive performance of commonly used in silico tools. Overall, REVEL and Meta-SNP had best balanced accuracy and might potentially be used at stronger evidence weighting than current ACMG/AMP prescription, in particular for predictions of benignity.
dc.languageen
dc.publisherElsevier BV
dc.subjectArticle
dc.subjectarticle
dc.titleClinical likelihood ratios and balanced accuracy for 44 in silico tools against multiple large-scale functional assays of cancer susceptibility genes.
dc.typeArticle
dc.date.updated2021-10-28T15:27:09Z
prism.endingPage2104
prism.issueIdentifier11
prism.publicationNameGenet Med
prism.startingPage2096
prism.volume23
dc.identifier.doi10.17863/CAM.77447
dcterms.dateAccepted2021-06-17
rioxxterms.versionofrecord10.1038/s41436-021-01265-z
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidCubuk, C [0000-0002-1734-5772]
dc.contributor.orcidTischkowitz, Marc [0000-0002-7880-0628]
dc.identifier.eissn1530-0366
pubs.funder-project-idCancer Research UK (C61296/A27223)


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