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A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog

Overview of attention for article published in Genome Biology (Online Edition), February 2018
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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 (98th percentile)

Citations

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58 Dimensions

Readers on

mendeley
117 Mendeley
citeulike
3 CiteULike
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Title
A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog
Published in
Genome Biology (Online Edition), February 2018
DOI 10.1186/s13059-018-1396-2
Pubmed ID
Authors

Joannella Morales, Danielle Welter, Emily H. Bowler, Maria Cerezo, Laura W. Harris, Aoife C. McMahon, Peggy Hall, Heather A. Junkins, Annalisa Milano, Emma Hastings, Cinzia Malangone, Annalisa Buniello, Tony Burdett, Paul Flicek, Helen Parkinson, Fiona Cunningham, Lucia A. Hindorff, Jacqueline A. L. MacArthur

Abstract

The accurate description of ancestry is essential to interpret, access, and integrate human genomics data, and to ensure that these benefit individuals from all ancestral backgrounds. However, there are no established guidelines for the representation of ancestry information. Here we describe a framework for the accurate and standardized description of sample ancestry, and validate it by application to the NHGRI-EBI GWAS Catalog. We confirm known biases and gaps in diversity, and find that African and Hispanic or Latin American ancestry populations contribute a disproportionately high number of associations. It is our hope that widespread adoption of this framework will lead to improved analysis, interpretation, and integration of human genomics data.

Twitter Demographics

The data shown below were collected from the profiles of 58 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 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 117 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 20%
Researcher 21 18%
Student > Master 13 11%
Student > Bachelor 13 11%
Other 8 7%
Other 20 17%
Unknown 19 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 30 26%
Agricultural and Biological Sciences 22 19%
Medicine and Dentistry 17 15%
Computer Science 4 3%
Economics, Econometrics and Finance 2 2%
Other 14 12%
Unknown 28 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 151. 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 October 2020.
All research outputs
#135,341
of 16,149,670 outputs
Outputs from Genome Biology (Online Edition)
#76
of 3,436 outputs
Outputs of similar age
#4,932
of 281,586 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 16,149,670 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 3,436 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.2. 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 281,586 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 98% 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