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WHAM!: a web-based visualization suite for user-defined analysis of metagenomic shotgun sequencing data

Overview of attention for article published in BMC Genomics, June 2018
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About this Attention Score

  • In the top 5% 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
69 tweeters

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
75 Mendeley
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Title
WHAM!: a web-based visualization suite for user-defined analysis of metagenomic shotgun sequencing data
Published in
BMC Genomics, June 2018
DOI 10.1186/s12864-018-4870-z
Pubmed ID
Authors

Joseph C. Devlin, Thomas Battaglia, Martin J. Blaser, Kelly V. Ruggles

Abstract

Exploration of large data sets, such as shotgun metagenomic sequence or expression data, by biomedical experts and medical professionals remains as a major bottleneck in the scientific discovery process. Although tools for this purpose exist for 16S ribosomal RNA sequencing analysis, there is a growing but still insufficient number of user-friendly interactive visualization workflows for easy data exploration and figure generation. The development of such platforms for this purpose is necessary to accelerate and streamline microbiome laboratory research. We developed the Workflow Hub for Automated Metagenomic Exploration (WHAM!) as a web-based interactive tool capable of user-directed data visualization and statistical analysis of annotated shotgun metagenomic and metatranscriptomic data sets. WHAM! includes exploratory and hypothesis-based gene and taxa search modules for visualizing differences in microbial taxa and gene family expression across experimental groups, and for creating publication quality figures without the need for command line interface or in-house bioinformatics. WHAM! is an interactive and customizable tool for downstream metagenomic and metatranscriptomic analysis providing a user-friendly interface allowing for easy data exploration by microbiome and ecological experts to facilitate discovery in multi-dimensional and large-scale data sets.

Twitter Demographics

The data shown below were collected from the profiles of 69 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 27%
Student > Ph. D. Student 13 17%
Student > Master 12 16%
Student > Postgraduate 5 7%
Student > Bachelor 4 5%
Other 9 12%
Unknown 12 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 27%
Biochemistry, Genetics and Molecular Biology 16 21%
Computer Science 5 7%
Medicine and Dentistry 4 5%
Immunology and Microbiology 4 5%
Other 6 8%
Unknown 20 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 42. 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 26 December 2018.
All research outputs
#690,452
of 19,474,859 outputs
Outputs from BMC Genomics
#102
of 9,805 outputs
Outputs of similar age
#18,251
of 293,093 outputs
Outputs of similar age from BMC Genomics
#1
of 6 outputs
Altmetric has tracked 19,474,859 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,805 research outputs from this source. They receive a mean Attention Score of 4.5. 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 293,093 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 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them