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VIPER: Visualization Pipeline for RNA-seq, a Snakemake workflow for efficient and complete RNA-seq analysis

Overview of attention for article published in BMC Bioinformatics, April 2018
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

blogs
1 blog
twitter
28 X users
patent
1 patent

Citations

dimensions_citation
158 Dimensions

Readers on

mendeley
260 Mendeley
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Title
VIPER: Visualization Pipeline for RNA-seq, a Snakemake workflow for efficient and complete RNA-seq analysis
Published in
BMC Bioinformatics, April 2018
DOI 10.1186/s12859-018-2139-9
Pubmed ID
Authors

MacIntosh Cornwell, Mahesh Vangala, Len Taing, Zachary Herbert, Johannes Köster, Bo Li, Hanfei Sun, Taiwen Li, Jian Zhang, Xintao Qiu, Matthew Pun, Rinath Jeselsohn, Myles Brown, X. Shirley Liu, Henry W. Long

Abstract

RNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology has led to the continuous development of new tools for every step of analysis from alignment to downstream pathway analysis. However, effectively using these analysis tools in a scalable and reproducible way can be challenging, especially for non-experts. Using the workflow management system Snakemake we have developed a user friendly, fast, efficient, and comprehensive pipeline for RNA-seq analysis. VIPER (Visualization Pipeline for RNA-seq analysis) is an analysis workflow that combines some of the most popular tools to take RNA-seq analysis from raw sequencing data, through alignment and quality control, into downstream differential expression and pathway analysis. VIPER has been created in a modular fashion to allow for the rapid incorporation of new tools to expand the capabilities. This capacity has already been exploited to include very recently developed tools that explore immune infiltrate and T-cell CDR (Complementarity-Determining Regions) reconstruction abilities. The pipeline has been conveniently packaged such that minimal computational skills are required to download and install the dozens of software packages that VIPER uses. VIPER is a comprehensive solution that performs most standard RNA-seq analyses quickly and effectively with a built-in capacity for customization and expansion.

X Demographics

X Demographics

The data shown below were collected from the profiles of 28 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 260 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 260 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 61 23%
Researcher 59 23%
Student > Master 17 7%
Student > Doctoral Student 16 6%
Student > Bachelor 14 5%
Other 23 9%
Unknown 70 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 82 32%
Agricultural and Biological Sciences 49 19%
Computer Science 16 6%
Medicine and Dentistry 12 5%
Immunology and Microbiology 8 3%
Other 23 9%
Unknown 70 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 26. 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 13 February 2020.
All research outputs
#1,315,892
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#181
of 7,400 outputs
Outputs of similar age
#30,704
of 330,413 outputs
Outputs of similar age from BMC Bioinformatics
#3
of 103 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 97% 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 330,413 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 90% of its contemporaries.
We're also able to compare this research output to 103 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 97% of its contemporaries.