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dc.contributor.authorSveinbjornsson, Gardar
dc.contributor.authorAlbrechtsen, Anders
dc.contributor.authorZink, Florian
dc.contributor.authorGudjonsson, Sigurjón A
dc.contributor.authorOddson, Asmundur
dc.contributor.authorMásson, Gísli
dc.contributor.authorHolm, Hilma
dc.contributor.authorKong, Augustine
dc.contributor.authorThorsteinsdottir, Unnur
dc.contributor.authorSulem, Patrick
dc.contributor.authorGudbjartsson, Daniel F
dc.contributor.authorStefansson, Kari
dc.date.accessioned2016-08-30T13:13:02Z
dc.date.available2016-08-30T13:13:02Z
dc.date.issued2016-03
dc.date.submitted2016
dc.identifier.citationWeighting sequence variants based on their annotation increases power of whole-genome association studies. 2016, 48 (3):314-7 Nat. Genet.en
dc.identifier.issn1546-1718
dc.identifier.pmid26854916
dc.identifier.doi10.1038/ng.3507
dc.identifier.urihttp://hdl.handle.net/2336/619045
dc.descriptionTo access publisher's full text version of this article click on the hyperlink at the bottom of the pageen
dc.description.abstractThe consensus approach to genome-wide association studies (GWAS) has been to assign equal prior probability of association to all sequence variants tested. However, some sequence variants, such as loss-of-function and missense variants, are more likely than others to affect protein function and are therefore more likely to be causative. Using data from whole-genome sequencing of 2,636 Icelanders and the association results for 96 quantitative and 123 binary phenotypes, we estimated the enrichment of association signals by sequence annotation. We propose a weighted Bonferroni adjustment that controls for the family-wise error rate (FWER), using as weights the enrichment of sequence annotations among association signals. We show that this weighted adjustment increases the power to detect association over the standard Bonferroni correction. We use the enrichment of associations by sequence annotation we have estimated in Iceland to derive significance thresholds for other populations with different numbers and combinations of sequence variants.
dc.language.isoenen
dc.publisherNatureen
dc.relation.urlhttp://dx.doi.org/ 10.1038/ng.3507en
dc.relation.urlhttp://www.nature.com/ng/journal/v48/n3/pdf/ng.3507.pdfen
dc.rightsArchived with thanks to Nature geneticsen
dc.subjectErfðafræðien
dc.subjectArfgengien
dc.subjectCAR12
dc.subject.meshGenome-Wide Association Studyen
dc.subject.meshHumansen
dc.subject.meshIcelanden
dc.subject.meshMolecular Sequence Annotationen
dc.subject.meshPhenotypeen
dc.subject.meshPolymorphism, Single Nucleotideen
dc.subject.meshSequence Analysis, DNAen
dc.titleWeighting sequence variants based on their annotation increases power of whole-genome association studies.en
dc.typeArticleen
dc.contributor.department1deCODE Genetics/Amgen, Inc., Reykjavik, Iceland. 2School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland. 3Bioinformatics Centre, Department of Biology, University of Copenhagen, Copenhagen, Denmark. 4Division of Cardiology, Department of Internal Medicine, Landspitali, National University Hospital of Iceland, Reykjavik, Iceland. 5Faculty of Medicine, University of Iceland, Reykjavik, Iceland.en
dc.identifier.journalNature geneticsen
dc.rights.accessLandspitali Access - LSH-aðganguren
html.description.abstractThe consensus approach to genome-wide association studies (GWAS) has been to assign equal prior probability of association to all sequence variants tested. However, some sequence variants, such as loss-of-function and missense variants, are more likely than others to affect protein function and are therefore more likely to be causative. Using data from whole-genome sequencing of 2,636 Icelanders and the association results for 96 quantitative and 123 binary phenotypes, we estimated the enrichment of association signals by sequence annotation. We propose a weighted Bonferroni adjustment that controls for the family-wise error rate (FWER), using as weights the enrichment of sequence annotations among association signals. We show that this weighted adjustment increases the power to detect association over the standard Bonferroni correction. We use the enrichment of associations by sequence annotation we have estimated in Iceland to derive significance thresholds for other populations with different numbers and combinations of sequence variants.


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