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PLoS One. 2017 Jan 3;12(1):e0168397. doi: 10.1371/journal.pone.0168397. eCollection 2017.

Metavisitor, a Suite of Galaxy Tools for Simple and Rapid Detection and Discovery of Viruses in Deep Sequence Data.

Author information

1
Institut Pasteur, Unit of Insect Vector Genetics and Genomics, Department of Parasites and Insect Vectors, Paris, FRANCE.
2
CNRS, Unit of Hosts, Vectors and Pathogens (URA3012), Paris, FRANCE.
3
Laboratory of Microbial Immunity, Singapore Immunology Network, A*STAR, 8A Biomedical Grove, Biopolis, Singapore, Singapore.
4
Sorbonne Universités, Université Pierre et Marie Curie (UPMC), CNRS, Institut de Biologie Paris Seine (IBPS), Developmental Biology Department, Paris, France.
5
Sorbonne Universités, Université Pierre et Marie Curie (UPMC), CNRS, Institut de Biologie Paris Seine (IBPS), ARTbio Bioinformatics Analysis Facility, Paris, France.
6
Department of Microbiology, University of Minnesota, Minneapolis, MN, United States of America.

Abstract

Metavisitor is a software package that allows biologists and clinicians without specialized bioinformatics expertise to detect and assemble viral genomes from deep sequence datasets. The package is composed of a set of modular bioinformatic tools and workflows that are implemented in the Galaxy framework. Using the graphical Galaxy workflow editor, users with minimal computational skills can use existing Metavisitor workflows or adapt them to suit specific needs by adding or modifying analysis modules. Metavisitor works with DNA, RNA or small RNA sequencing data over a range of read lengths and can use a combination of de novo and guided approaches to assemble genomes from sequencing reads. We show that the software has the potential for quick diagnosis as well as discovery of viruses from a vast array of organisms. Importantly, we provide here executable Metavisitor use cases, which increase the accessibility and transparency of the software, ultimately enabling biologists or clinicians to focus on biological or medical questions.

PMID:
28045932
PMCID:
PMC5207757
DOI:
10.1371/journal.pone.0168397
[Indexed for MEDLINE]
Free PMC Article

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