Geographic Population Structure Analysis of Worldwide Human Populations Infers their Biogeographical Origins
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Fecha
2014-04-29Autor(es)
Elhaik, Eran
Tatarinova, Tatiana
Chebotarev, Dmitri
Piras, Ignazio S.
Calo, Carla Maria
De Montis, Antonella
Atzori, Manuela
Marini, Monica
Tofanelli, Sergio
Francalacci, Paolo
Pagani, Luca
Tyler-Smith, Chris
Xue, Yali
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
Ganesh Prasad, ArunKumar
Hammer, Michael
Matisoo-Smith, Lisa
Wells, R. Spencer
Metadatos
Mostrar el registro completo del ítemResumen
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 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.
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