↓ Skip to main content

Reconstruction of Ribosomal RNA Genes from Metagenomic Data

Overview of attention for article published in PLOS ONE, June 2012
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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

blogs
1 blog
twitter
18 X users

Citations

dimensions_citation
51 Dimensions

Readers on

mendeley
171 Mendeley
citeulike
5 CiteULike
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
Reconstruction of Ribosomal RNA Genes from Metagenomic Data
Published in
PLOS ONE, June 2012
DOI 10.1371/journal.pone.0039948
Pubmed ID
Authors

Lu Fan, Kerensa McElroy, Torsten Thomas

Abstract

Direct sequencing of environmental DNA (metagenomics) has a great potential for describing the 16S rRNA gene diversity of microbial communities. However current approaches using this 16S rRNA gene information to describe community diversity suffer from low taxonomic resolution or chimera problems. Here we describe a new strategy that involves stringent assembly and data filtering to reconstruct full-length 16S rRNA genes from metagenomicpyrosequencing data. Simulations showed that reconstructed 16S rRNA genes provided a true picture of the community diversity, had minimal rates of chimera formation and gave taxonomic resolution down to genus level. The strategy was furthermore compared to PCR-based methods to determine the microbial diversity in two marine sponges. This showed that about 30% of the abundant phylotypes reconstructed from metagenomic data failed to be amplified by PCR. Our approach is readily applicable to existing metagenomic datasets and is expected to lead to the discovery of new microbial phylotypes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 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 171 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 6%
Brazil 4 2%
Germany 3 2%
France 2 1%
Sweden 2 1%
Norway 1 <1%
Colombia 1 <1%
South Africa 1 <1%
India 1 <1%
Other 9 5%
Unknown 137 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 53 31%
Student > Ph. D. Student 38 22%
Student > Master 26 15%
Student > Postgraduate 11 6%
Student > Doctoral Student 11 6%
Other 27 16%
Unknown 5 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 102 60%
Biochemistry, Genetics and Molecular Biology 19 11%
Environmental Science 19 11%
Immunology and Microbiology 7 4%
Medicine and Dentistry 3 2%
Other 10 6%
Unknown 11 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 25 May 2013.
All research outputs
#2,119,157
of 24,953,268 outputs
Outputs from PLOS ONE
#26,229
of 216,204 outputs
Outputs of similar age
#12,690
of 169,521 outputs
Outputs of similar age from PLOS ONE
#415
of 4,013 outputs
Altmetric has tracked 24,953,268 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 216,204 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.7. This one has done well, scoring higher than 87% 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 169,521 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 92% of its contemporaries.
We're also able to compare this research output to 4,013 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.