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Using multi-way admixture mapping to elucidate TB susceptibility in the South African Coloured population

Overview of attention for article published in BMC Genomics, November 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
2 X users

Citations

dimensions_citation
34 Dimensions

Readers on

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47 Mendeley
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Title
Using multi-way admixture mapping to elucidate TB susceptibility in the South African Coloured population
Published in
BMC Genomics, November 2014
DOI 10.1186/1471-2164-15-1021
Pubmed ID
Authors

Michelle Daya, Lize van der Merwe, Christopher R Gignoux, Paul D van Helden, Marlo Möller, Eileen G Hoal

Abstract

The admixed South African Coloured population is ideally suited to the discovery of tuberculosis susceptibility genetic variants and their probable ethnic origins, but previous attempts at finding such variants using genome-wide admixture mapping were hampered by the inaccuracy of local ancestry inference. In this study, we infer local ancestry using the novel algorithm implemented in RFMix, with the emphasis on identifying regions of excess San or Bantu ancestry, which we hypothesize may harbour TB susceptibility genes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 2%
South Africa 1 2%
Unknown 45 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 23%
Student > Ph. D. Student 10 21%
Student > Master 5 11%
Professor 4 9%
Other 2 4%
Other 5 11%
Unknown 10 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 26%
Agricultural and Biological Sciences 9 19%
Medicine and Dentistry 6 13%
Philosophy 2 4%
Immunology and Microbiology 2 4%
Other 5 11%
Unknown 11 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 28 June 2015.
All research outputs
#1,337,753
of 22,771,140 outputs
Outputs from BMC Genomics
#267
of 10,641 outputs
Outputs of similar age
#19,616
of 361,642 outputs
Outputs of similar age from BMC Genomics
#5
of 248 outputs
Altmetric has tracked 22,771,140 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,641 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 97% 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 361,642 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 94% of its contemporaries.
We're also able to compare this research output to 248 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.