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Estimation of viral richness from shotgun metagenomes using a frequency count approach

Overview of attention for article published in Microbiome, February 2013
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  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Average Attention Score compared to outputs of the same age and source

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9 X users

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103 Mendeley
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Title
Estimation of viral richness from shotgun metagenomes using a frequency count approach
Published in
Microbiome, February 2013
DOI 10.1186/2049-2618-1-5
Pubmed ID
Authors

Heather K Allen, John Bunge, James A Foster, Darrell O Bayles, Thaddeus B Stanton

Abstract

Viruses are important drivers of ecosystem functions, yet little is known about the vast majority of viruses. Viral shotgun metagenomics enables the investigation of broad ecological questions in phage communities. One ecological characteristic is species richness, which is the number of different species in a community. Viruses do not have a phylogenetic marker analogous to the bacterial 16S rRNA gene with which to estimate richness, and so contig spectra are employed to measure the number of virus taxa in a given community. A contig spectrum is generated from a viral shotgun metagenome by assembling the random sequence reads into groups of sequences that overlap (contigs) and counting the number of sequences that group within each contig. Current tools available to analyze contig spectra to estimate phage richness are limited by relying on rank-abundance data.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 4 4%
United States 3 3%
United Kingdom 2 2%
South Africa 1 <1%
Spain 1 <1%
Turkey 1 <1%
Unknown 91 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 31%
Researcher 23 22%
Student > Master 9 9%
Student > Doctoral Student 8 8%
Student > Bachelor 5 5%
Other 12 12%
Unknown 14 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 55%
Biochemistry, Genetics and Molecular Biology 9 9%
Environmental Science 8 8%
Immunology and Microbiology 5 5%
Computer Science 3 3%
Other 6 6%
Unknown 15 15%
Attention Score in Context

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 19 April 2019.
All research outputs
#5,667,659
of 22,694,633 outputs
Outputs from Microbiome
#1,214
of 1,420 outputs
Outputs of similar age
#60,979
of 283,057 outputs
Outputs of similar age from Microbiome
#5
of 10 outputs
Altmetric has tracked 22,694,633 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,420 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 40.1. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
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 283,057 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 78% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.