↓ Skip to main content

RiboTagger: fast and unbiased 16S/18S profiling using whole community shotgun metagenomic or metatranscriptome surveys

Overview of attention for article published in BMC Bioinformatics, December 2016
Altmetric Badge

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 (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

blogs
1 blog
twitter
40 X users

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
116 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
RiboTagger: fast and unbiased 16S/18S profiling using whole community shotgun metagenomic or metatranscriptome surveys
Published in
BMC Bioinformatics, December 2016
DOI 10.1186/s12859-016-1378-x
Pubmed ID
Authors

Chao Xie, Chin Lui Wesley Goi, Daniel H. Huson, Peter F. R. Little, Rohan B. H. Williams

Abstract

Taxonomic profiling of microbial communities is often performed using small subunit ribosomal RNA (SSU) amplicon sequencing (16S or 18S), while environmental shotgun sequencing is often focused on functional analysis. Large shotgun datasets contain a significant number of SSU sequences and these can be exploited to perform an unbiased SSU--based taxonomic analysis. Here we present a new program called RiboTagger that identifies and extracts taxonomically informative ribotags located in a specified variable region of the SSU gene in a high-throughput fashion. RiboTagger permits fast recovery of SSU-RNA sequences from shotgun nucleic acid surveys of complex microbial communities. The program targets all three domains of life, exhibits high sensitivity and specificity and is substantially faster than comparable programs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 40 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 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 113 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 25%
Student > Ph. D. Student 25 22%
Student > Master 13 11%
Student > Doctoral Student 9 8%
Other 8 7%
Other 16 14%
Unknown 16 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 45 39%
Biochemistry, Genetics and Molecular Biology 20 17%
Immunology and Microbiology 10 9%
Environmental Science 9 8%
Computer Science 5 4%
Other 6 5%
Unknown 21 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 30. 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 14 October 2019.
All research outputs
#1,278,227
of 24,885,505 outputs
Outputs from BMC Bioinformatics
#142
of 7,601 outputs
Outputs of similar age
#26,587
of 431,950 outputs
Outputs of similar age from BMC Bioinformatics
#2
of 132 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,601 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. 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 431,950 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 93% of its contemporaries.
We're also able to compare this research output to 132 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 99% of its contemporaries.