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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 (98th percentile)

Mentioned by

blogs
1 blog
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48 X users

Readers on

mendeley
87 Mendeley
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Article details
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
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.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 48 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 87 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 20 23%
Student > Ph. D. Student 16 18%
Student > Master 13 15%
Professor > Associate Professor 5 6%
Student > Postgraduate 5 6%
Other 10 11%
Unknown 18 21%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 22 25%
Biochemistry, Genetics and Molecular Biology 21 24%
Computer Science 5 6%
Immunology and Microbiology 4 5%
Medicine and Dentistry 4 5%
Other 7 8%
Unknown 24 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 32. 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
#1,579,931
of 34,441,029 outputs
Outputs from BMC Genomics
#233
of 12,989 outputs
Outputs of similar age
#25,294
of 373,666 outputs
Outputs of similar age from BMC Genomics
#3
of 207 outputs
Altmetric has tracked 34,441,029 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,989 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. 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 373,666 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 207 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 98% of its contemporaries.