Geographic population structure analysis of worldwide human populations infers their biogeographical origins
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- dc.contributor.author Elhaik, Eranca
- dc.contributor.author Comas, David, 1969-ca
- dc.contributor.author Bertranpetit, Jaume, 1952-ca
- dc.contributor.author Martínez Cruz, Begoñaca
- dc.contributor.author Wells, R. Spencerca
- dc.contributor.author Genographic Consortiumca
- dc.date.accessioned 2015-06-16T08:18:40Z
- dc.date.available 2015-06-16T08:18:40Z
- dc.date.issued 2014ca
- dc.description.abstract The search for a method that utilizes biological information to predict humans’ place of origin has occupied scientists for millennia. Over the past four decades, scientists have employed genetic data in an effort to achieve this goal but with limited success. While biogeographical algorithms using next-generation sequencing data have achieved an accuracy of 700 km in Europe, they were inaccurate elsewhere. Here we describe the Geographic Population Structure (GPS) algorithm and demonstrate its accuracy with three data sets using 40,000–130,000 SNPs. GPS placed 83% of worldwide individuals in their country of origin. Applied to over 200 Sardinians villagers, GPS placed a quarter of them in their villages and most of the rest within 50 km of their villages. GPS’s accuracy and power to infer the biogeography of worldwide individuals down to their country or, in some cases, village, of origin, underscores the promise of admixture-based methods for biogeography and has ramifications for genetic ancestry testing.en
- dc.description.sponsorship E.E is supported in part by Genographic grant GP 01/n-/n12. L.P, C.T.S and Y.X were/nsupported by The Wellcome Trust (098051). O.B. was supported in part by Presidium/nRAS (MCB programme) and RFBR (13-04-01711). T.T. was supported by grants from/nThe National Institute for General Medical Studies (GM068968), and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD070996). S.T. is supported by a PRIN2009 grant. The Genographic Project is supported by the National Geographic Society IBM and the Waitt Foundation.en
- dc.format.mimetype application/pdfca
- dc.identifier.citation Elhaik E, Tatarinova T, Chebotarev D, Piras IS, Calo CM, De Montis A et al. Geographic population structure analysis of worldwide human populations infers their biogeographical origins. Nature communications. 2014;5:3513. DOI: 10.1038/ncomms4513ca
- dc.identifier.doi http://dx.doi.org/10.1038/ncomms4513
- dc.identifier.issn 2041-1723ca
- dc.identifier.uri http://hdl.handle.net/10230/23833
- dc.language.iso engca
- dc.publisher Nature Publishing Groupca
- dc.relation.ispartof Nature communications. 2014;5:3513
- dc.rights © Nature Publishing Group. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the materialen
- dc.rights.accessRights info:eu-repo/semantics/openAccessca
- dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/
- dc.subject.keyword Biological sciencesen
- dc.subject.keyword Geneticsen
- dc.subject.other Genètica de poblacions humanesca
- dc.subject.other Genètica humana -- Variacióca
- dc.title Geographic population structure analysis of worldwide human populations infers their biogeographical originsen
- dc.type info:eu-repo/semantics/articleca
- dc.type.version info:eu-repo/semantics/publishedVersionca