Show simple item record

dc.contributor.authorGreene, Danielen
dc.contributor.authorNIHR, BioResourceen
dc.contributor.authorRichardson, Sylviaen
dc.contributor.authorTurro Bassols, Ernesten
dc.date.accessioned2016-01-14T16:04:20Z
dc.date.available2016-01-14T16:04:20Z
dc.date.issued2016-03-03en
dc.identifier.citationD. Greene et al. The American Journal of Human Genetics (2016). volume 98, issue 3: pp. 490-499. DOI:10.1016/j.ajhg.2016.01.008en
dc.identifier.issn0002-9297
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/253282
dc.description.abstractRare genetic disorders, which can now be studied systematically with affordable genome sequencing, are often caused by high-penetrance rare variants. Such disorders are often heterogeneous and characterised by abnormalities spanning multiple organ systems ascertained with variable clinical precision. Existing methods for identifying genes with variants responsible for rare diseases summarise phenotypes with unstructured binary or quantitative variables. The Human Phenotype Ontology (HPO) allows composite phenotypes to be represented systematically but association methods accounting for the ontological relationship between HPO terms do not exist. We present a Bayesian method to model the association between an HPO-coded patient phenotype and genotype. Our method estimates the probability of an association together with an HPO-coded phenotype characteristic of the disease. We thus formalise a clinical approach to phenotyping that is lacking in standard regression techniques for rare disease research. We demonstrate the power of our method by uncovering a number of true associations in a large collection of genome-sequenced and HPO-coded cases with rare diseases.
dc.description.sponsorshipThis work was supported by NIHR award RG65966 (D.G. and E.T.) and the Medical Research Council programme grant MC UP 0801/1 (D.G. and S.R.). The NIHR BioResource – Rare Diseases projects were approved by Research Ethics Committees in the UK and appropriate national ethics authorities in non-UK enrolment centres (see Supplemental Note). We are grateful to Dr William J Astle for advice on the statistical model and for providing comments on the manuscript. We are particularly thankful to the BPD project members for granting access to detailed HPO terms of patients
dc.languageEnglishen
dc.language.isoenen
dc.publisherElsevier
dc.rightsAttribution 2.0 UK: England & Wales*
dc.rights.urihttp://creativecommons.org/licenses/by/2.0/uk/*
dc.titlePhenotype similarity regression for identifying the genetic determinants of rare diseasesen
dc.typeArticle
dc.description.versionThis is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ajhg.2016.01.008en
prism.endingPage499
prism.publicationDate2016en
prism.publicationNameThe American Journal of Human Geneticsen
prism.startingPage490
prism.volume98en
dc.rioxxterms.funderNIHR
dc.rioxxterms.funderMRC
dc.rioxxterms.projectidRG65966
dc.rioxxterms.projectidMC UP 0801/1
dcterms.dateAccepted2016-01-08en
rioxxterms.versionofrecord10.1016/j.ajhg.2016.01.008en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2016-03-03en
dc.contributor.orcidRichardson, Sylvia [0000-0003-1998-492X]
dc.contributor.orcidTurro Bassols, Ernest [0000-0002-1820-6563]
dc.identifier.eissn1537-6605
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idMRC (1381192)
pubs.funder-project-idMRC (1185)
pubs.funder-project-idCambridge University Hospitals NHS Foundation Trust (CUH) (BRC)
cam.orpheus.successThu Jan 30 12:55:24 GMT 2020 - The item has an open VoR version.*
rioxxterms.freetoread.startdate2300-01-01


Files in this item

Thumbnail
Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record

Attribution 2.0 UK: England & Wales
Except where otherwise noted, this item's licence is described as Attribution 2.0 UK: England & Wales