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dc.contributor.authorHernández, N.
dc.contributor.authorSoenksen, J.
dc.contributor.authorNewcombe, P.
dc.contributor.authorSandhu, M.
dc.contributor.authorBarroso, I.
dc.contributor.authorWallace, C.
dc.contributor.authorAsimit, J. L.
dc.date.accessioned2021-10-22T15:51:34Z
dc.date.available2021-10-22T15:51:34Z
dc.date.issued2021-10-22
dc.date.submitted2021-04-14
dc.identifier.others41467-021-26364-y
dc.identifier.other26364
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/329778
dc.descriptionFunder: “Expanding excellence in England” award from Research England
dc.description.abstractAbstract: Joint fine-mapping that leverages information between quantitative traits could improve accuracy and resolution over single-trait fine-mapping. Using summary statistics, flashfm (flexible and shared information fine-mapping) fine-maps signals for multiple traits, allowing for missing trait measurements and use of related individuals. In a Bayesian framework, prior model probabilities are formulated to favour model combinations that share causal variants to capitalise on information between traits. Simulation studies demonstrate that both approaches produce broadly equivalent results when traits have no shared causal variants. When traits share at least one causal variant, flashfm reduces the number of potential causal variants by 30% compared with single-trait fine-mapping. In a Ugandan cohort with 33 cardiometabolic traits, flashfm gave a 20% reduction in the total number of potential causal variants from single-trait fine-mapping. Here we show flashfm is computationally efficient and can easily be deployed across publicly available summary statistics for signals in up to six traits.
dc.languageen
dc.publisherNature Publishing Group UK
dc.subjectArticle
dc.subject/631/208/205/2138
dc.subject/631/208/480
dc.subject/45/43
dc.subject/141
dc.subject/139
dc.subjectarticle
dc.titleThe flashfm approach for fine-mapping multiple quantitative traits
dc.typeArticle
dc.date.updated2021-10-22T15:51:33Z
prism.issueIdentifier1
prism.publicationNameNature Communications
prism.volume12
dc.identifier.doi10.17863/CAM.77223
dcterms.dateAccepted2021-10-04
rioxxterms.versionofrecord10.1038/s41467-021-26364-y
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidHernández, N. [0000-0002-0710-5652]
dc.contributor.orcidSoenksen, J. [0000-0002-4361-4200]
dc.contributor.orcidBarroso, I. [0000-0001-5800-4520]
dc.contributor.orcidWallace, C. [0000-0001-9755-1703]
dc.contributor.orcidAsimit, J. L. [0000-0002-4857-2249]
dc.identifier.eissn2041-1723
pubs.funder-project-idRCUK | Medical Research Council (MRC) (MC UU 00002/9, MC_UU_00002/4, MR/R021368/1)
pubs.funder-project-idDH | National Institute for Health Research (NIHR) (BRC-1215-20014, BRC-1215-20014, BRC-1215-20014)
pubs.funder-project-idWellcome Trust (Wellcome) (WT107881)


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