Geographic population structure analysis of worldwide human populations infers their biogeographical origins
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Geographic population structure analysis of worldwide human populations infers their biogeographical origins. / Elhaik, Eran; Tatarinova, Tatiana; Chebotarev, Dmitri; Piras, Ignazio S.; Calò, Carla Maria; De Montis, Antonella; Atzori, Manuela; Marini, Monica; Tofanelli, Sergio; Francalacci, Paolo; Pagani, Luca; Tyler-Smith, Chris; Xue, Yali; Cucca, Francesco; Schurr, Theodore G.; Gaieski, Jill B.; Melendez, Carlalynne; Vilar, Miguel G.; Owings, Amanda C.; Gómez, Rocío; Fujita, Ricardo; Santos, Fabrício R.; Comas, David; Balanovsky, Oleg; Balanovska, Elena; Zalloua, Pierre; Soodyall, Himla; Pitchappan, Ramasamy; Prasad, Arun Kumar Ganesh; Hammer, Michael; Matisoo-Smith, Lisa; Wells, R. Spencer; Acosta, Oscar; Adhikarla, Syama; Adler, Christina J.; Bertranpetit, Jaume; Clarke, Andrew C.; Cooper, Alan; Der Sarkissian, Clio S.I.; Haak, Wolfgang; Haber, Marc; Jin, Li; Kaplan, Matthew E.; Li, Hui; Li, Shilin; Martínez-Cruz, Begoña; Merchant, Nirav C.; Mitchell, John R.; Parida, Laxmi; Platt, Daniel E.; Quintana-Murci, Lluis; Renfrew, Colin; Lacerda, Daniela R.; Royyuru, Ajay K.; Sandoval, Jose Raul; Santhakumari, Arun Varatharajan; Hernanz, David F.Soria; Swamikrishnan, Pandikumar; Ziegle, Janet S.
In: Nature Communications, Vol. 5, 3513, 29.04.2014.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Geographic population structure analysis of worldwide human populations infers their biogeographical origins
AU - Elhaik, Eran
AU - Tatarinova, Tatiana
AU - Chebotarev, Dmitri
AU - Piras, Ignazio S.
AU - Calò, Carla Maria
AU - De Montis, Antonella
AU - Atzori, Manuela
AU - Marini, Monica
AU - Tofanelli, Sergio
AU - Francalacci, Paolo
AU - Pagani, Luca
AU - Tyler-Smith, Chris
AU - Xue, Yali
AU - Cucca, Francesco
AU - Schurr, Theodore G.
AU - Gaieski, Jill B.
AU - Melendez, Carlalynne
AU - Vilar, Miguel G.
AU - Owings, Amanda C.
AU - Gómez, Rocío
AU - Fujita, Ricardo
AU - Santos, Fabrício R.
AU - Comas, David
AU - Balanovsky, Oleg
AU - Balanovska, Elena
AU - Zalloua, Pierre
AU - Soodyall, Himla
AU - Pitchappan, Ramasamy
AU - Prasad, Arun Kumar Ganesh
AU - Hammer, Michael
AU - Matisoo-Smith, Lisa
AU - Wells, R. Spencer
AU - Acosta, Oscar
AU - Adhikarla, Syama
AU - Adler, Christina J.
AU - Bertranpetit, Jaume
AU - Clarke, Andrew C.
AU - Cooper, Alan
AU - Der Sarkissian, Clio S.I.
AU - Haak, Wolfgang
AU - Haber, Marc
AU - Jin, Li
AU - Kaplan, Matthew E.
AU - Li, Hui
AU - Li, Shilin
AU - Martínez-Cruz, Begoña
AU - Merchant, Nirav C.
AU - Mitchell, John R.
AU - Parida, Laxmi
AU - Platt, Daniel E.
AU - Quintana-Murci, Lluis
AU - Renfrew, Colin
AU - Lacerda, Daniela R.
AU - Royyuru, Ajay K.
AU - Sandoval, Jose Raul
AU - Santhakumari, Arun Varatharajan
AU - Hernanz, David F.Soria
AU - Swamikrishnan, Pandikumar
AU - Ziegle, Janet S.
PY - 2014/4/29
Y1 - 2014/4/29
N2 - 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 700km 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 50km 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.
AB - 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 700km 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 50km 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.
UR - http://www.scopus.com/inward/record.url?scp=84899845427&partnerID=8YFLogxK
U2 - 10.1038/ncomms4513
DO - 10.1038/ncomms4513
M3 - Article
C2 - 24781250
AN - SCOPUS:84899845427
VL - 5
JO - Nature Communications
JF - Nature Communications
SN - 2041-1723
M1 - 3513
ER -