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RCAS: an RNA centric annotation system for transcriptome-wide regions of interest
In the field of RNA, the technologies for studying the transcriptome have created a tremendous potential for deciphering the puzzles of the RNA biology. Along with the excitement, the unprecedented volume of RNA related omics data is creating great challenges in bioinformatics analyses. Here, we pre...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5449606/ https://www.ncbi.nlm.nih.gov/pubmed/28334930 http://dx.doi.org/10.1093/nar/gkx120 |
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author | Uyar, Bora Yusuf, Dilmurat Wurmus, Ricardo Rajewsky, Nikolaus Ohler, Uwe Akalin, Altuna |
author_facet | Uyar, Bora Yusuf, Dilmurat Wurmus, Ricardo Rajewsky, Nikolaus Ohler, Uwe Akalin, Altuna |
author_sort | Uyar, Bora |
collection | PubMed |
description | In the field of RNA, the technologies for studying the transcriptome have created a tremendous potential for deciphering the puzzles of the RNA biology. Along with the excitement, the unprecedented volume of RNA related omics data is creating great challenges in bioinformatics analyses. Here, we present the RNA Centric Annotation System (RCAS), an R package, which is designed to ease the process of creating gene-centric annotations and analysis for the genomic regions of interest obtained from various RNA-based omics technologies. The design of RCAS is modular, which enables flexible usage and convenient integration with other bioinformatics workflows. RCAS is an R/Bioconductor package but we also created graphical user interfaces including a Galaxy wrapper and a stand-alone web service. The application of RCAS on published datasets shows that RCAS is not only able to reproduce published findings but also helps generate novel knowledge and hypotheses. The meta-gene profiles, gene-centric annotation, motif analysis and gene-set analysis provided by RCAS provide contextual knowledge which is necessary for understanding the functional aspects of different biological events that involve RNAs. In addition, the array of different interfaces and deployment options adds the convenience of use for different levels of users. RCAS is available at http://bioconductor.org/packages/release/bioc/html/RCAS.html and http://rcas.mdc-berlin.de. |
format | Online Article Text |
id | pubmed-5449606 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-54496062017-06-05 RCAS: an RNA centric annotation system for transcriptome-wide regions of interest Uyar, Bora Yusuf, Dilmurat Wurmus, Ricardo Rajewsky, Nikolaus Ohler, Uwe Akalin, Altuna Nucleic Acids Res Methods Online In the field of RNA, the technologies for studying the transcriptome have created a tremendous potential for deciphering the puzzles of the RNA biology. Along with the excitement, the unprecedented volume of RNA related omics data is creating great challenges in bioinformatics analyses. Here, we present the RNA Centric Annotation System (RCAS), an R package, which is designed to ease the process of creating gene-centric annotations and analysis for the genomic regions of interest obtained from various RNA-based omics technologies. The design of RCAS is modular, which enables flexible usage and convenient integration with other bioinformatics workflows. RCAS is an R/Bioconductor package but we also created graphical user interfaces including a Galaxy wrapper and a stand-alone web service. The application of RCAS on published datasets shows that RCAS is not only able to reproduce published findings but also helps generate novel knowledge and hypotheses. The meta-gene profiles, gene-centric annotation, motif analysis and gene-set analysis provided by RCAS provide contextual knowledge which is necessary for understanding the functional aspects of different biological events that involve RNAs. In addition, the array of different interfaces and deployment options adds the convenience of use for different levels of users. RCAS is available at http://bioconductor.org/packages/release/bioc/html/RCAS.html and http://rcas.mdc-berlin.de. Oxford University Press 2017-06-02 2017-02-21 /pmc/articles/PMC5449606/ /pubmed/28334930 http://dx.doi.org/10.1093/nar/gkx120 Text en © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Methods Online Uyar, Bora Yusuf, Dilmurat Wurmus, Ricardo Rajewsky, Nikolaus Ohler, Uwe Akalin, Altuna RCAS: an RNA centric annotation system for transcriptome-wide regions of interest |
title | RCAS: an RNA centric annotation system for transcriptome-wide regions of interest |
title_full | RCAS: an RNA centric annotation system for transcriptome-wide regions of interest |
title_fullStr | RCAS: an RNA centric annotation system for transcriptome-wide regions of interest |
title_full_unstemmed | RCAS: an RNA centric annotation system for transcriptome-wide regions of interest |
title_short | RCAS: an RNA centric annotation system for transcriptome-wide regions of interest |
title_sort | rcas: an rna centric annotation system for transcriptome-wide regions of interest |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5449606/ https://www.ncbi.nlm.nih.gov/pubmed/28334930 http://dx.doi.org/10.1093/nar/gkx120 |
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