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A general linear model-based approach for inferring selection to climate

Overview of attention for article published in BMC Genetics, September 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)

Mentioned by

twitter
13 tweeters

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
50 Mendeley
citeulike
2 CiteULike
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Title
A general linear model-based approach for inferring selection to climate
Published in
BMC Genetics, September 2013
DOI 10.1186/1471-2156-14-87
Pubmed ID
Authors

Srilakshmi M Raj, Luca Pagani, Irene Gallego Romero, Toomas Kivisild, William Amos

Abstract

Many efforts have been made to detect signatures of positive selection in the human genome, especially those associated with expansion from Africa and subsequent colonization of all other continents. However, most approaches have not directly probed the relationship between the environment and patterns of variation among humans. We have designed a method to identify regions of the genome under selection based on Mantel tests conducted within a general linear model framework, which we call MAntel-GLM to Infer Clinal Selection (MAGICS). MAGICS explicitly incorporates population-specific and genome-wide patterns of background variation as well as information from environmental values to provide an improved picture of selection and its underlying causes in human populations.

Twitter Demographics

The data shown below were collected from the profiles of 13 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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Brazil 1 2%
Germany 1 2%
Canada 1 2%
United Kingdom 1 2%
Unknown 44 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 30%
Student > Ph. D. Student 8 16%
Student > Bachelor 6 12%
Student > Master 5 10%
Professor > Associate Professor 4 8%
Other 4 8%
Unknown 8 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 54%
Biochemistry, Genetics and Molecular Biology 6 12%
Medicine and Dentistry 3 6%
Engineering 2 4%
Earth and Planetary Sciences 1 2%
Other 2 4%
Unknown 9 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 30 September 2013.
All research outputs
#5,007,831
of 21,347,849 outputs
Outputs from BMC Genetics
#157
of 1,055 outputs
Outputs of similar age
#41,994
of 186,266 outputs
Outputs of similar age from BMC Genetics
#1
of 1 outputs
Altmetric has tracked 21,347,849 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,055 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 85% 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 186,266 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them