Evaluating the accuracy of imputation methods in a five-way admixed population

dc.contributor.authorSchurz, Haikoen_ZA
dc.contributor.authorMuller, Stephanie J.en_ZA
dc.contributor.authorVan Helden, Paul Daviden_ZA
dc.contributor.authorTromp, Gerarden_ZA
dc.contributor.authorHoal, Eileen G.en_ZA
dc.contributor.authorKinnear, Craig J.en_ZA
dc.contributor.authorMoller, Marloen_ZA
dc.date.accessioned2019-02-25T12:10:44Z
dc.date.available2019-02-25T12:10:44Z
dc.date.issued2019
dc.descriptionCITATION: Schurz, H., et al. 2019. Evaluating the accuracy of imputation methods in a five-way admixed population. Frontiers in Genetics, 10:34, doi:10.3389/fgene.2019.00034.
dc.descriptionThe original publication is available at https://www.frontiersin.org
dc.descriptionPublication of this article was funded by the Stellenbosch University Open Access Fund.
dc.description.abstractGenotype imputation is a powerful tool for increasing statistical power in an association analysis. Meta-analysis of multiple study datasets also requires a substantial overlap of SNPs for a successful association analysis, which can be achieved by imputation. Quality of imputed datasets is largely dependent on the software used, as well as the reference populations chosen. The accuracy of imputation of available reference populations has not been tested for the five-way admixed South African Colored (SAC) population. In this study, imputation results obtained using three freely-accessible methods were evaluated for accuracy and quality. We show that the African Genome Resource is the best reference panel for imputation of missing genotypes in samples from the SAC population, implemented via the freely accessible Sanger Imputation Server.en_ZA
dc.description.urihttps://www.frontiersin.org/articles/10.3389/fgene.2019.00034/full
dc.description.versionPublisher's version
dc.format.extent9 pages
dc.identifier.citationSchurz, H., et al. 2019. Evaluating the accuracy of imputation methods in a five-way admixed population. Frontiers in Genetics, 10:34, doi:10.3389/fgene.2019.00034
dc.identifier.issn1664-8021(online)
dc.identifier.otherdoi:10.3389/fgene.2019.00034
dc.identifier.urihttp://hdl.handle.net/10019.1/105467
dc.language.isoen_ZAen_ZA
dc.publisherFrontiers Media
dc.rights.holderAuthors retain copyright
dc.subjectMultiple imputation (Statistics)en_ZA
dc.titleEvaluating the accuracy of imputation methods in a five-way admixed populationen_ZA
dc.typeArticleen_ZA
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