Title |
VIPER: Visualization Pipeline for RNA-seq, a Snakemake workflow for efficient and complete RNA-seq analysis
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Published in |
BMC Bioinformatics, April 2018
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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
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 8 | 29% |
Germany | 3 | 11% |
United Kingdom | 2 | 7% |
Taiwan | 2 | 7% |
Canada | 1 | 4% |
Netherlands | 1 | 4% |
Ukraine | 1 | 4% |
Spain | 1 | 4% |
Sweden | 1 | 4% |
Other | 1 | 4% |
Unknown | 7 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 18 | 64% |
Members of the public | 10 | 36% |
Mendeley readers
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% |