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Geographic population structure analysis of worldwide human populations infers their biogeographical origins

Overview of attention for article published in Nature Communications, April 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
29 news outlets
blogs
13 blogs
twitter
76 tweeters
peer_reviews
1 peer review site
weibo
1 weibo user
facebook
3 Facebook pages
googleplus
2 Google+ users
reddit
1 Redditor
video
1 video uploader

Readers on

mendeley
274 Mendeley
citeulike
5 CiteULike
Title
Geographic population structure analysis of worldwide human populations infers their biogeographical origins
Published in
Nature Communications, April 2014
DOI 10.1038/ncomms4513
Pubmed ID
Authors

Eran Elhaik, Tatiana Tatarinova, Dmitri Chebotarev, Ignazio S. Piras, Carla Maria Calò, Antonella De Montis, Manuela Atzori, Monica Marini, Sergio Tofanelli, Paolo Francalacci, Luca Pagani, Chris Tyler-Smith, Yali Xue, Francesco Cucca, Theodore G. Schurr, Jill B. Gaieski, Carlalynne Melendez, Miguel G. Vilar, Amanda C. Owings, Rocío Gómez, Ricardo Fujita, Fabrício R. Santos, David Comas, Oleg Balanovsky, Elena Balanovska, Pierre Zalloua, Himla Soodyall, Ramasamy Pitchappan, ArunKumar GaneshPrasad, Michael Hammer, Lisa Matisoo-Smith, R. Spencer Wells, The Genographic Consortium, Elhaik E, Tatarinova T, Chebotarev D, Piras IS, Maria Calò C, De Montis A, Atzori M, Marini M, Tofanelli S, Francalacci P, Pagani L, Tyler-Smith C, Xue Y, Cucca F, Schurr TG, Gaieski JB, Melendez C, Vilar MG, Owings AC, Gómez R, Fujita R, Santos FR, Comas D, Balanovsky O, Balanovska E, Zalloua P, Soodyall H, Pitchappan R, Ganeshprasad A, Hammer M, Matisoo-Smith L, Wells RS, Oscar Acosta, Syama Adhikarla, Christina J. Adler, Jaume Bertranpetit, Andrew C. Clarke, Alan Cooper, Clio S. I. Der Sarkissian, Wolfgang Haak, Marc Haber, Li Jin, Matthew E. Kaplan, Hui Li, Shilin Li, Begoña Martínez-Cruz, Nirav C. Merchant, John R. Mitchell, Laxmi Parida, Daniel E. Platt, Lluis Quintana-Murci, Colin Renfrew, Daniela R. Lacerda, Ajay K. Royyuru, Jose Raul Sandoval, Arun Varatharajan Santhakumari, David F. Soria Hernanz, Pandikumar Swamikrishnan, Janet S. Ziegle, Dmitr i Chebotarev,

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.

Twitter Demographics

The data shown below were collected from the profiles of 76 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 274 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 11 4%
Germany 4 1%
United Kingdom 4 1%
Spain 2 <1%
Mexico 2 <1%
Italy 2 <1%
Brazil 2 <1%
Philippines 2 <1%
Sweden 2 <1%
Other 3 1%
Unknown 240 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 73 27%
Student > Ph. D. Student 66 24%
Student > Master 35 13%
Student > Bachelor 21 8%
Other 17 6%
Other 62 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 148 54%
Biochemistry, Genetics and Molecular Biology 40 15%
Medicine and Dentistry 18 7%
Unspecified 15 5%
Computer Science 13 5%
Other 40 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 388. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 July 2018.
All research outputs
#20,518
of 11,495,147 outputs
Outputs from Nature Communications
#284
of 17,439 outputs
Outputs of similar age
#318
of 186,396 outputs
Outputs of similar age from Nature Communications
#10
of 495 outputs
Altmetric has tracked 11,495,147 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,439 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 46.9. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 186,396 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 495 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.