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gbtools: Interactive Visualization of Metagenome Bins in R

Overview of attention for article published in Frontiers in Microbiology, December 2015
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

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Title
gbtools: Interactive Visualization of Metagenome Bins in R
Published in
Frontiers in Microbiology, December 2015
DOI 10.3389/fmicb.2015.01451
Pubmed ID
Authors

Brandon K B Seah, Harald R Gruber-Vodicka

Abstract

Improvements in DNA sequencing technology have increased the amount and quality of sequences that can be obtained from metagenomic samples, making it practical to extract individual microbial genomes from metagenomic assemblies ("binning"). However, while many tools and methods exist for unsupervised binning with various statistical algorithms, there are few options for visualizing the results, even though visualization is vital to exploratory data analysis. We have developed gbtools, a software package that allows users to visualize metagenomic assemblies by plotting coverage (sequencing depth) and GC values of contigs, and also to annotate the plots with taxonomic information. Different sets of annotations, including taxonomic assignments from conserved marker genes or SSU rRNA genes, can be imported simultaneously; users can choose which annotations to plot. Bins can be manually defined from plots, or be imported from third-party binning tools and overlaid onto plots, such that results from different methods can be compared side-by-side. gbtools reports summary statistics of bins including marker gene completeness, and allows the user to add or subtract bins with each other. We illustrate some of the functions available in gbtools with two examples: the metagenome of Olavius algarvensis, a marine oligochaete worm that has up to five bacterial symbionts, and the metagenome of a synthetic mock community comprising 64 bacterial and archaeal strains. We show how instances of poor automated binning, sequencer GC% bias, and variation between samples can be quickly diagnosed by visualization, and demonstrate how the results from different binning tools can be combined and refined to yield manually curated bins with higher completeness. gbtools is open-source and written in R. The software package, documentation, and example data are available freely online at https://github.com/kbseah/genome-bin-tools.

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X Demographics

The data shown below were collected from the profiles of 36 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 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Brazil 2 2%
Germany 1 <1%
Australia 1 <1%
Spain 1 <1%
United Kingdom 1 <1%
Unknown 97 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 27%
Researcher 25 24%
Student > Master 12 11%
Student > Bachelor 7 7%
Student > Doctoral Student 7 7%
Other 18 17%
Unknown 8 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 40 38%
Biochemistry, Genetics and Molecular Biology 27 26%
Environmental Science 11 10%
Computer Science 4 4%
Earth and Planetary Sciences 4 4%
Other 8 8%
Unknown 11 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 22 February 2016.
All research outputs
#1,886,169
of 24,965,047 outputs
Outputs from Frontiers in Microbiology
#1,278
of 28,551 outputs
Outputs of similar age
#31,843
of 400,143 outputs
Outputs of similar age from Frontiers in Microbiology
#22
of 393 outputs
Altmetric has tracked 24,965,047 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 28,551 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 particularly well, scoring higher than 95% 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 400,143 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 393 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 94% of its contemporaries.