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Tentacle: distributed quantification of genes in metagenomes

Overview of attention for article published in Giga Science, September 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
25 X users
peer_reviews
1 peer review site
facebook
2 Facebook pages
googleplus
2 Google+ users

Readers on

mendeley
44 Mendeley
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Title
Tentacle: distributed quantification of genes in metagenomes
Published in
Giga Science, September 2015
DOI 10.1186/s13742-015-0078-1
Pubmed ID
Authors

Fredrik Boulund, Anders Sjögren, Erik Kristiansson

Abstract

In metagenomics, microbial communities are sequenced at increasingly high resolution, generating datasets with billions of DNA fragments. Novel methods that can efficiently process the growing volumes of sequence data are necessary for the accurate analysis and interpretation of existing and upcoming metagenomes. Here we present Tentacle, which is a novel framework that uses distributed computational resources for gene quantification in metagenomes. Tentacle is implemented using a dynamic master-worker approach in which DNA fragments are streamed via a network and processed in parallel on worker nodes. Tentacle is modular, extensible, and comes with support for six commonly used sequence aligners. It is easy to adapt Tentacle to different applications in metagenomics and easy to integrate into existing workflows. Evaluations show that Tentacle scales very well with increasing computing resources. We illustrate the versatility of Tentacle on three different use cases. Tentacle is written for Linux in Python 2.7 and is published as open source under the GNU General Public License (v3). Documentation, tutorials, installation instructions, and the source code are freely available online at: http://bioinformatics.math.chalmers.se/tentacle.

X Demographics

X Demographics

The data shown below were collected from the profiles of 25 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 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 5%
Ireland 1 2%
Sweden 1 2%
United Kingdom 1 2%
Japan 1 2%
United States 1 2%
Unknown 37 84%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 25%
Researcher 10 23%
Student > Bachelor 7 16%
Student > Master 4 9%
Student > Doctoral Student 3 7%
Other 8 18%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 39%
Biochemistry, Genetics and Molecular Biology 8 18%
Computer Science 6 14%
Mathematics 3 7%
Immunology and Microbiology 3 7%
Other 6 14%
Unknown 1 2%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 September 2015.
All research outputs
#2,312,600
of 25,593,129 outputs
Outputs from Giga Science
#464
of 1,174 outputs
Outputs of similar age
#29,973
of 279,416 outputs
Outputs of similar age from Giga Science
#9
of 16 outputs
Altmetric has tracked 25,593,129 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,174 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.7. This one has gotten more attention than average, scoring higher than 60% 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 279,416 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 89% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.