Title |
VING: a software for visualization of deep sequencing signals
|
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Published in |
BMC Research Notes, September 2015
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DOI | 10.1186/s13104-015-1404-5 |
Pubmed ID | |
Authors |
Marc Descrimes, Yousra Ben Zouari, Maxime Wery, Rachel Legendre, Daniel Gautheret, Antonin Morillon |
Abstract |
Next generation sequencing (NGS) data treatment often requires mapping sequenced reads onto a reference genome for further analysis. Mapped data are commonly visualized using genome browsers. However, such software are not suited for a publication-ready and versatile representation of NGS data coverage, especially when multiple experiments are simultaneously treated. We developed 'VING', a stand-alone R script that takes as input NGS mapping files and genome annotations to produce accurate snapshots of the NGS coverage signal for any specified genomic region. VING offers multiple viewing options, including strand-specific views and a special heatmap mode for representing multiple experiments in a single figure. VING produces high-quality figures for NGS data representation in a genome region of interest. It is available at http://vm-gb.curie.fr/ving/ . We also developed a Galaxy wrapper, available in the Galaxy tool shed with installation and usage instructions. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 3 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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China | 2 | 7% |
France | 2 | 7% |
Germany | 1 | 3% |
United States | 1 | 3% |
Luxembourg | 1 | 3% |
Unknown | 23 | 77% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 11 | 37% |
Student > Ph. D. Student | 8 | 27% |
Student > Master | 4 | 13% |
Other | 2 | 7% |
Professor > Associate Professor | 2 | 7% |
Other | 1 | 3% |
Unknown | 2 | 7% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 13 | 43% |
Biochemistry, Genetics and Molecular Biology | 4 | 13% |
Computer Science | 3 | 10% |
Medicine and Dentistry | 2 | 7% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
Other | 2 | 7% |
Unknown | 5 | 17% |