dc.contributor.author | Whiffin, N | |
dc.contributor.author | Walsh, R | |
dc.contributor.author | Govind, R | |
dc.contributor.author | Edwards, M | |
dc.contributor.author | Ahmad, M | |
dc.contributor.author | Zhang, X | |
dc.contributor.author | Tayal, U | |
dc.contributor.author | Buchan, R | |
dc.contributor.author | Midwinter, W | |
dc.contributor.author | Wilk, AE | |
dc.contributor.author | Najgebauer, H | |
dc.contributor.author | Francis, C | |
dc.contributor.author | Wilkinson, S | |
dc.contributor.author | Monk, T | |
dc.contributor.author | Brett, L | |
dc.contributor.author | O'Regan, DP | |
dc.contributor.author | Prasad, SK | |
dc.contributor.author | Morris-Rosendahl, DJ | |
dc.contributor.author | Barton, PJR | |
dc.contributor.author | Edwards, E | |
dc.contributor.author | Ware, JS | |
dc.contributor.author | Cook, SA | |
dc.date.accessioned | 2019-02-20T07:51:06Z | |
dc.date.issued | 2018-10-01 | |
dc.identifier.citation | Genetics in medicine : official journal of the American College of Medical Genetics, 2018, 20 (10), pp. 1246 - 1254 | |
dc.identifier.issn | 1098-3600 | |
dc.identifier.uri | https://repository.icr.ac.uk/handle/internal/3066 | |
dc.identifier.eissn | 1530-0366 | |
dc.identifier.doi | 10.1038/gim.2017.258 | |
dc.description.abstract | PURPOSE: Internationally adopted variant interpretation guidelines from the American College of Medical Genetics and Genomics (ACMG) are generic and require disease-specific refinement. Here we developed CardioClassifier ( http://www.cardioclassifier.org ), a semiautomated decision-support tool for inherited cardiac conditions (ICCs). METHODS: CardioClassifier integrates data retrieved from multiple sources with user-input case-specific information, through an interactive interface, to support variant interpretation. Combining disease- and gene-specific knowledge with variant observations in large cohorts of cases and controls, we refined 14 computational ACMG criteria and created three ICC-specific rules. RESULTS: We benchmarked CardioClassifier on 57 expertly curated variants and show full retrieval of all computational data, concordantly activating 87.3% of rules. A generic annotation tool identified fewer than half as many clinically actionable variants (64/219 vs. 156/219, Fisher's P = 1.1 × 10-18), with important false positives, illustrating the critical importance of disease and gene-specific annotations. CardioClassifier identified putatively disease-causing variants in 33.7% of 327 cardiomyopathy cases, comparable with leading ICC laboratories. Through addition of manually curated data, variants found in over 40% of cardiomyopathy cases are fully annotated, without requiring additional user-input data. CONCLUSION: CardioClassifier is an ICC-specific decision-support tool that integrates expertly curated computational annotations with case-specific data to generate fast, reproducible, and interactive variant pathogenicity reports, according to best practice guidelines. | |
dc.format | Print-Electronic | |
dc.format.extent | 1246 - 1254 | |
dc.language | eng | |
dc.language.iso | eng | |
dc.publisher | NATURE PUBLISHING GROUP | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | |
dc.subject | Humans | |
dc.subject | Cardiovascular Abnormalities | |
dc.subject | Computational Biology | |
dc.subject | Genomics | |
dc.subject | Mutation | |
dc.subject | Genome, Human | |
dc.subject | Decision Support Techniques | |
dc.subject | Software | |
dc.subject | Genetic Testing | |
dc.subject | High-Throughput Nucleotide Sequencing | |
dc.title | CardioClassifier: disease- and gene-specific computational decision support for clinical genome interpretation. | |
dc.type | Journal Article | |
dcterms.dateAccepted | 2017-12-05 | |
rioxxterms.versionofrecord | 10.1038/gim.2017.258 | |
rioxxterms.licenseref.uri | https://creativecommons.org/licenses/by/4.0 | |
rioxxterms.licenseref.startdate | 2018-10 | |
rioxxterms.type | Journal Article/Review | |
dc.relation.isPartOf | Genetics in medicine : official journal of the American College of Medical Genetics | |
pubs.issue | 10 | |
pubs.notes | Not known | |
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/Molecular Pathology | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Molecular Pathology/Molecular & Population Genetics | |
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/Molecular Pathology | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Molecular Pathology/Molecular & Population Genetics | |
pubs.publication-status | Published | |
pubs.volume | 20 | |
pubs.embargo.terms | Not known | |
icr.researchteam | Molecular & Population Genetics | |
dc.contributor.icrauthor | Whiffin, Nicola | |