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Clinical Sequencing Uncovers Origins and Evolution of Lassa Virus

Overview of attention for article published in Cell, August 2015
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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 (91st percentile)

Mentioned by

news
8 news outlets
blogs
2 blogs
twitter
114 tweeters
facebook
11 Facebook pages
googleplus
2 Google+ users
reddit
2 Redditors
video
1 video uploader

Readers on

mendeley
121 Mendeley
citeulike
2 CiteULike
Title
Clinical Sequencing Uncovers Origins and Evolution of Lassa Virus
Published in
Cell, August 2015
DOI 10.1016/j.cell.2015.07.020
Pubmed ID
Authors

Andersen, Kristian G, Shapiro, B Jesse, Matranga, Christian B, Sealfon, Rachel, Lin, Aaron E, Moses, Lina M, Folarin, Onikepe A, Goba, Augustine, Odia, Ikponmwonsa, Ehiane, Philomena E, Momoh, Mambu, England, Eleina M, Winnicki, Sarah, Branco, Luis M, Gire, Stephen K, Phelan, Eric, Tariyal, Ridhi, Tewhey, Ryan, Omoniwa, Omowunmi, Fullah, Mohammed, Fonnie, Richard, Fonnie, Mbalu, Kanneh, Lansana, Jalloh, Simbirie, Gbakie, Michael, Saffa, Sidiki, Karbo, Kandeh, Gladden, Adrianne D, Qu, James, Stremlau, Matthew, Nekoui, Mahan, Finucane, Hilary K, Tabrizi, Shervin, Vitti, Joseph J, Birren, Bruce, Fitzgerald, Michael, McCowan, Caryn, Ireland, Andrea, Berlin, Aaron M, Bochicchio, James, Tazon-Vega, Barbara, Lennon, Niall J, Ryan, Elizabeth M, Bjornson, Zach, Milner, Danny A, Lukens, Amanda K, Broodie, Nisha, Rowland, Megan, Heinrich, Megan, Akdag, Marjan, Schieffelin, John S, Levy, Danielle, Akpan, Henry, Bausch, Daniel G, Rubins, Kathleen, McCormick, Joseph B, Lander, Eric S, Günther, Stephan, Hensley, Lisa, Okogbenin, Sylvanus, , , Schaffner, Stephen F, Okokhere, Peter O, Khan, S Humarr, Grant, Donald S, Akpede, George O, Asogun, Danny A, Gnirke, Andreas, Levin, Joshua Z, Happi, Christian T, Garry, Robert F, Sabeti, Pardis C, Kristian G. Andersen, B. Jesse Shapiro, Christian B. Matranga, Rachel Sealfon, Aaron E. Lin, Lina M. Moses, Onikepe A. Folarin, Augustine Goba, Ikponmwonsa Odia, Philomena E. Ehiane, Mambu Momoh, Eleina M. England, Sarah Winnicki, Luis M. Branco, Stephen K. Gire, Eric Phelan, Ridhi Tariyal, Ryan Tewhey, Omowunmi Omoniwa, Mohammed Fullah, Richard Fonnie, Mbalu Fonnie, Lansana Kanneh, Simbirie Jalloh, Michael Gbakie, Sidiki Saffa, Kandeh Karbo, Adrianne D. Gladden, James Qu, Matthew Stremlau, Mahan Nekoui, Hilary K. Finucane, Shervin Tabrizi, Joseph J. Vitti, Bruce Birren, Michael Fitzgerald, Caryn McCowan, Andrea Ireland, Aaron M. Berlin, James Bochicchio, Barbara Tazon-Vega, Niall J. Lennon, Elizabeth M. Ryan, Zach Bjornson, Danny A. Milner, Amanda K. Lukens, Nisha Broodie, Megan Rowland, Megan Heinrich, Marjan Akdag, John S. Schieffelin, Danielle Levy, Henry Akpan, Daniel G. Bausch, Kathleen Rubins, Joseph B. McCormick, Eric S. Lander, Stephan Günther, Lisa Hensley, Sylvanus Okogbenin, Stephen F. Schaffner, Peter O. Okokhere, S. Humarr Khan, Donald S. Grant, George O. Akpede, Danny A. Asogun, Andreas Gnirke, Joshua Z. Levin, Christian T. Happi, Robert F. Garry, Pardis C. Sabeti

Abstract

The 2013-2015 West African epidemic of Ebola virus disease (EVD) reminds us of how little is known about biosafety level 4 viruses. Like Ebola virus, Lassa virus (LASV) can cause hemorrhagic fever with high case fatality rates. We generated a genomic catalog of almost 200 LASV sequences from clinical and rodent reservoir samples. We show that whereas the 2013-2015 EVD epidemic is fueled by human-to-human transmissions, LASV infections mainly result from reservoir-to-human infections. We elucidated the spread of LASV across West Africa and show that this migration was accompanied by changes in LASV genome abundance, fatality rates, codon adaptation, and translational efficiency. By investigating intrahost evolution, we found that mutations accumulate in epitopes of viral surface proteins, suggesting selection for immune escape. This catalog will serve as a foundation for the development of vaccines and diagnostics. VIDEO ABSTRACT.

Twitter Demographics

The data shown below were collected from the profiles of 114 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 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 3 2%
United States 2 2%
Spain 1 <1%
Germany 1 <1%
United Kingdom 1 <1%
Japan 1 <1%
Netherlands 1 <1%
Unknown 111 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 26%
Researcher 26 21%
Student > Master 15 12%
Student > Postgraduate 10 8%
Librarian 9 7%
Other 29 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 72 60%
Biochemistry, Genetics and Molecular Biology 17 14%
Medicine and Dentistry 12 10%
Immunology and Microbiology 7 6%
Nursing and Health Professions 4 3%
Other 9 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 156. 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 29 July 2016.
All research outputs
#37,802
of 7,406,533 outputs
Outputs from Cell
#230
of 8,829 outputs
Outputs of similar age
#1,801
of 225,059 outputs
Outputs of similar age from Cell
#15
of 179 outputs
Altmetric has tracked 7,406,533 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 8,829 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.3. 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 225,059 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 179 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 91% of its contemporaries.