dc.contributor.author | Cubuk, C | |
dc.contributor.author | Garrett, A | |
dc.contributor.author | Choi, S | |
dc.contributor.author | King, L | |
dc.contributor.author | Loveday, C | |
dc.contributor.author | Torr, B | |
dc.contributor.author | Burghel, GJ | |
dc.contributor.author | Durkie, M | |
dc.contributor.author | Callaway, A | |
dc.contributor.author | Robinson, R | |
dc.contributor.author | Drummond, J | |
dc.contributor.author | Berry, I | |
dc.contributor.author | Wallace, A | |
dc.contributor.author | Eccles, D | |
dc.contributor.author | Tischkowitz, M | |
dc.contributor.author | Whiffin, N | |
dc.contributor.author | Ware, JS | |
dc.contributor.author | Hanson, H | |
dc.contributor.author | Turnbull, C | |
dc.contributor.author | CanVIG-Uk, | |
dc.date.accessioned | 2021-07-08T08:57:59Z | |
dc.date.available | 2021-07-08T08:57:59Z | |
dc.date.issued | 2021-07-06 | |
dc.identifier.citation | Genetics in Medicine | |
dc.identifier.issn | 1098-3600 | |
dc.identifier.uri | https://repository.icr.ac.uk/handle/internal/4673 | |
dc.identifier.eissn | 1530-0366 | |
dc.identifier.doi | 10.1038/s41436-021-01265-z | |
dc.description.abstract | PURPOSE: 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.language | eng | |
dc.language.iso | eng | |
dc.publisher | ELSEVIER SCIENCE INC | |
dc.relation.isreplacedby | internal/4681 | |
dc.relation.isreplacedby | https://repository.icr.ac.uk/handle/internal/4681 | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | |
dc.title | Clinical likelihood ratios and balanced accuracy for 44 in silico tools against multiple large-scale functional assays of cancer susceptibility genes. | |
dc.type | Journal Article | |
dcterms.dateAccepted | 2021-06-17 | |
rioxxterms.version | VoR | |
rioxxterms.versionofrecord | 10.1038/s41436-021-01265-z | |
rioxxterms.licenseref.uri | https://creativecommons.org/licenses/by/4.0 | |
rioxxterms.type | Journal Article/Review | |
dc.relation.isPartOf | Genetics in Medicine | |
pubs.notes | No embargo | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/Students | |
pubs.organisational-group | /ICR/Students/PhD and MPhil | |
pubs.organisational-group | /ICR/Students/PhD and MPhil/20/21 Starting Cohort | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/Students | |
pubs.organisational-group | /ICR/Students/PhD and MPhil | |
pubs.organisational-group | /ICR/Students/PhD and MPhil/20/21 Starting Cohort | |
pubs.publication-status | Published online | |
pubs.embargo.terms | No embargo | |
dc.contributor.icrauthor | Garrett, Alice | |
dc.contributor.icrauthor | Choi, Subin | |
dc.contributor.icrauthor | Pemberton - Whiteley, Bethany | |
dc.contributor.icrauthor | Turnbull, Clare | |