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Assembly of viral genomes from metagenomes

Overview of attention for article published in Frontiers in Microbiology, December 2014
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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13 X users

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225 Mendeley
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Title
Assembly of viral genomes from metagenomes
Published in
Frontiers in Microbiology, December 2014
DOI 10.3389/fmicb.2014.00714
Pubmed ID
Authors

Saskia L. Smits, Rogier Bodewes, Aritz Ruiz-Gonzalez, Wolfgang Baumgärtner, Marion P. Koopmans, Albert D. M. E. Osterhaus, Anita C. Schürch

Abstract

Viral infections remain a serious global health issue. Metagenomic approaches are increasingly used in the detection of novel viral pathogens but also to generate complete genomes of uncultivated viruses. In silico identification of complete viral genomes from sequence data would allow rapid phylogenetic characterization of these new viruses. Often, however, complete viral genomes are not recovered, but rather several distinct contigs derived from a single entity are, some of which have no sequence homology to any known proteins. De novo assembly of single viruses from a metagenome is challenging, not only because of the lack of a reference genome, but also because of intrapopulation variation and uneven or insufficient coverage. Here we explored different assembly algorithms, remote homology searches, genome-specific sequence motifs, k-mer frequency ranking, and coverage profile binning to detect and obtain viral target genomes from metagenomes. All methods were tested on 454-generated sequencing datasets containing three recently described RNA viruses with a relatively large genome which were divergent to previously known viruses from the viral families Rhabdoviridae and Coronaviridae. Depending on specific characteristics of the target virus and the metagenomic community, different assembly and in silico gap closure strategies were successful in obtaining near complete viral genomes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 225 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 7 3%
United States 4 2%
United Kingdom 2 <1%
Switzerland 1 <1%
Sweden 1 <1%
Egypt 1 <1%
Germany 1 <1%
Belgium 1 <1%
Slovenia 1 <1%
Other 0 0%
Unknown 206 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 62 28%
Researcher 62 28%
Student > Master 29 13%
Student > Bachelor 13 6%
Professor > Associate Professor 9 4%
Other 20 9%
Unknown 30 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 96 43%
Biochemistry, Genetics and Molecular Biology 41 18%
Immunology and Microbiology 17 8%
Medicine and Dentistry 15 7%
Engineering 8 4%
Other 12 5%
Unknown 36 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 26 April 2015.
All research outputs
#4,477,809
of 24,885,505 outputs
Outputs from Frontiers in Microbiology
#4,257
of 28,434 outputs
Outputs of similar age
#58,869
of 364,635 outputs
Outputs of similar age from Frontiers in Microbiology
#40
of 233 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 28,434 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has done well, scoring higher than 84% 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 364,635 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 83% of its contemporaries.
We're also able to compare this research output to 233 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.