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Analysis of protein-coding genetic variation in 60,706 humans

Overview of attention for article published in Nature, August 2016
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  • 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 (96th percentile)

Citations

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5987 Dimensions

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3918 Mendeley
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22 CiteULike
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Title
Analysis of protein-coding genetic variation in 60,706 humans
Published in
Nature, August 2016
DOI 10.1038/nature19057
Pubmed ID
Authors

Monkol Lek, Konrad J. Karczewski, Eric V. Minikel, Kaitlin E. Samocha, Eric Banks, Timothy Fennell, Anne H. O’Donnell-Luria, James S. Ware, Andrew J. Hill, Beryl B. Cummings, Taru Tukiainen, Daniel P. Birnbaum, Jack A. Kosmicki, Laramie E. Duncan, Karol Estrada, Fengmei Zhao, James Zou, Emma Pierce-Hoffman, Joanne Berghout, David N. Cooper, Nicole Deflaux, Mark DePristo, Ron Do, Jason Flannick, Menachem Fromer, Laura Gauthier, Jackie Goldstein, Namrata Gupta, Daniel Howrigan, Adam Kiezun, Mitja I. Kurki, Ami Levy Moonshine, Pradeep Natarajan, Lorena Orozco, Gina M. Peloso, Ryan Poplin, Manuel A. Rivas, Valentin Ruano-Rubio, Samuel A. Rose, Douglas M. Ruderfer, Khalid Shakir, Peter D. Stenson, Christine Stevens, Brett P. Thomas, Grace Tiao, Maria T. Tusie-Luna, Ben Weisburd, Hong-Hee Won, Dongmei Yu, David M. Altshuler, Diego Ardissino, Michael Boehnke, John Danesh, Stacey Donnelly, Roberto Elosua, Jose C. Florez, Stacey B. Gabriel, Gad Getz, Stephen J. Glatt, Christina M. Hultman, Sekar Kathiresan, Markku Laakso, Steven McCarroll, Mark I. McCarthy, Dermot McGovern, Ruth McPherson, Benjamin M. Neale, Aarno Palotie, Shaun M. Purcell, Danish Saleheen, Jeremiah M. Scharf, Pamela Sklar, Patrick F. Sullivan, Jaakko Tuomilehto, Ming T. Tsuang, Hugh C. Watkins, James G. Wilson, Mark J. Daly, Daniel G. MacArthur

Abstract

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

Twitter Demographics

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The data shown below were compiled from readership statistics for 3,918 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 21 <1%
United Kingdom 11 <1%
Italy 8 <1%
Spain 6 <1%
France 4 <1%
Denmark 3 <1%
Netherlands 3 <1%
Germany 3 <1%
Sweden 3 <1%
Other 29 <1%
Unknown 3827 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 923 24%
Researcher 841 21%
Student > Master 459 12%
Student > Bachelor 365 9%
Other 229 6%
Other 687 18%
Unknown 414 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1351 34%
Agricultural and Biological Sciences 899 23%
Medicine and Dentistry 545 14%
Computer Science 144 4%
Neuroscience 134 3%
Other 282 7%
Unknown 563 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 936. 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 21 July 2020.
All research outputs
#7,288
of 15,875,387 outputs
Outputs from Nature
#1,018
of 75,793 outputs
Outputs of similar age
#222
of 267,716 outputs
Outputs of similar age from Nature
#36
of 995 outputs
Altmetric has tracked 15,875,387 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 75,793 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 85.8. 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 267,716 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 995 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 96% of its contemporaries.