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viRome: an R package for the visualization and analysis of viral small RNA sequence datasets

Summary: RNA interference (RNAi) is known to play an important part in defence against viruses in a range of species. Second-generation sequencing technologies allow us to assay these systems and the small RNAs that play a key role with unprecedented depth. However, scientists need access to tools t...

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Detalles Bibliográficos
Autores principales: Watson, Mick, Schnettler, Esther, Kohl, Alain
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3712215/
https://www.ncbi.nlm.nih.gov/pubmed/23709497
http://dx.doi.org/10.1093/bioinformatics/btt297
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author Watson, Mick
Schnettler, Esther
Kohl, Alain
author_facet Watson, Mick
Schnettler, Esther
Kohl, Alain
author_sort Watson, Mick
collection PubMed
description Summary: RNA interference (RNAi) is known to play an important part in defence against viruses in a range of species. Second-generation sequencing technologies allow us to assay these systems and the small RNAs that play a key role with unprecedented depth. However, scientists need access to tools that can condense, analyse and display the resulting data. Here, we present viRome, a package for R that takes aligned sequence data and produces a range of essential plots and reports. Availability and implementation: viRome is released under the BSD license as a package for R available for both Windows and Linux http://virome.sf.net. Additional information and a tutorial is available on the ARK-Genomics website: http://www.ark-genomics.org/bioinformatics/virome. Contact: mick.watson@roslin.ed.ac.uk
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spelling pubmed-37122152013-07-17 viRome: an R package for the visualization and analysis of viral small RNA sequence datasets Watson, Mick Schnettler, Esther Kohl, Alain Bioinformatics Applications Notes Summary: RNA interference (RNAi) is known to play an important part in defence against viruses in a range of species. Second-generation sequencing technologies allow us to assay these systems and the small RNAs that play a key role with unprecedented depth. However, scientists need access to tools that can condense, analyse and display the resulting data. Here, we present viRome, a package for R that takes aligned sequence data and produces a range of essential plots and reports. Availability and implementation: viRome is released under the BSD license as a package for R available for both Windows and Linux http://virome.sf.net. Additional information and a tutorial is available on the ARK-Genomics website: http://www.ark-genomics.org/bioinformatics/virome. Contact: mick.watson@roslin.ed.ac.uk Oxford University Press 2013-08-01 2013-05-24 /pmc/articles/PMC3712215/ /pubmed/23709497 http://dx.doi.org/10.1093/bioinformatics/btt297 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Watson, Mick
Schnettler, Esther
Kohl, Alain
viRome: an R package for the visualization and analysis of viral small RNA sequence datasets
title viRome: an R package for the visualization and analysis of viral small RNA sequence datasets
title_full viRome: an R package for the visualization and analysis of viral small RNA sequence datasets
title_fullStr viRome: an R package for the visualization and analysis of viral small RNA sequence datasets
title_full_unstemmed viRome: an R package for the visualization and analysis of viral small RNA sequence datasets
title_short viRome: an R package for the visualization and analysis of viral small RNA sequence datasets
title_sort virome: an r package for the visualization and analysis of viral small rna sequence datasets
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3712215/
https://www.ncbi.nlm.nih.gov/pubmed/23709497
http://dx.doi.org/10.1093/bioinformatics/btt297
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