↓ Skip to main content

Taxonomic and Functional Compositions Impacted by the Quality of Metatranscriptomic Assemblies

Overview of attention for article published in Frontiers in Microbiology, June 2018
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 (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

blogs
1 blog
twitter
10 X users

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
79 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
Taxonomic and Functional Compositions Impacted by the Quality of Metatranscriptomic Assemblies
Published in
Frontiers in Microbiology, June 2018
DOI 10.3389/fmicb.2018.01235
Pubmed ID
Authors

Maggie C. Y. Lau, Rachel L. Harris, Youmi Oh, Min Joo Yi, Aida Behmard, Tullis C. Onstott

Abstract

Metatranscriptomics has recently been applied to investigate the active biogeochemical processes and elemental cycles, and in situ responses of microbiomes to environmental stimuli and stress factors. De novo assembly of RNA-Sequencing (RNA-Seq) data can reveal a more detailed description of the metabolic interactions amongst the active microbial communities. However, the quality of the assemblies and the depiction of the metabolic network provided by various de novo assemblers have not yet been thoroughly assessed. In this study, we compared 15 de novo metatranscriptomic assemblies for a fracture fluid sample collected from a borehole located at 1.34 km below land surface in a South African gold mine. These assemblies were constructed from total, non-coding, and coding reads using five de novo transcriptomic assemblers (Trans-ABySS, Trinity, Oases, IDBA-tran, and Rockhopper). They were evaluated based on the number of transcripts, transcript length, range of transcript coverage, continuity, percentage of transcripts with confident annotation assignments, as well as taxonomic and functional diversity patterns. The results showed that these parameters varied considerably among the assemblies, with Trans-ABySS and Trinity generating the best assemblies for non-coding and coding RNA reads, respectively, because the high number of transcripts assembled covered a wide expression range, and captured extensively the taxonomic and metabolic gene diversity, respectively. We concluded that the choice of de novo transcriptomic assemblers impacts substantially the taxonomic and functional compositions. Care should be taken to obtain high-quality assemblies for informing the in situ metabolic landscape.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 79 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 24%
Researcher 19 24%
Student > Master 12 15%
Professor > Associate Professor 5 6%
Student > Postgraduate 4 5%
Other 9 11%
Unknown 11 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 24%
Agricultural and Biological Sciences 19 24%
Environmental Science 15 19%
Immunology and Microbiology 4 5%
Engineering 2 3%
Other 5 6%
Unknown 15 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 12 July 2018.
All research outputs
#3,130,333
of 25,728,350 outputs
Outputs from Frontiers in Microbiology
#2,580
of 29,739 outputs
Outputs of similar age
#59,751
of 342,528 outputs
Outputs of similar age from Frontiers in Microbiology
#90
of 710 outputs
Altmetric has tracked 25,728,350 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 29,739 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done particularly well, scoring higher than 91% 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 342,528 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 82% of its contemporaries.
We're also able to compare this research output to 710 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.