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ARPIR: automatic RNA-Seq pipelines with interactive report
BACKGROUND: RNA-Seq is an increasing used methodology to study either coding and non-coding RNA expression. There are many software tools available for each phase of the RNA-Seq analysis and each of them uses different algorithms. Furthermore, the analysis consists of several steps regarding alignme...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751108/ https://www.ncbi.nlm.nih.gov/pubmed/33349239 http://dx.doi.org/10.1186/s12859-020-03846-2 |
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author | Spinozzi, Giulio Tini, Valentina Adorni, Alessia Falini, Brunangelo Martelli, Maria Paola |
author_facet | Spinozzi, Giulio Tini, Valentina Adorni, Alessia Falini, Brunangelo Martelli, Maria Paola |
author_sort | Spinozzi, Giulio |
collection | PubMed |
description | BACKGROUND: RNA-Seq is an increasing used methodology to study either coding and non-coding RNA expression. There are many software tools available for each phase of the RNA-Seq analysis and each of them uses different algorithms. Furthermore, the analysis consists of several steps regarding alignment (primary-analysis), quantification, differential analysis (secondary-analysis) and any tertiary-analysis and can therefore be time-consuming to deal with each step separately, in addition to requiring a computer knowledge. For this reason, the development of an automated pipeline that allows the entire analysis to be managed through a single initial command and that is easy to use even for those without computer skills can be useful. Faced with the vast availability of RNA-Seq analysis tools, it is first of all necessary to select a limited number of pipelines to include. For this purpose, we compared eight pipelines obtained by combining the most used tools and for each one we evaluated peak of RAM, time, sensitivity and specificity. RESULTS: The pipeline with shorter times, lower consumption of RAM and higher sensitivity is the one consisting in HISAT2 for alignment, featureCounts for quantification and edgeR for differential analysis. Here, we developed ARPIR, an automated pipeline that recurs by default to the cited pipeline, but it also allows to choose, between different tools, those of the pipelines having the best performances. CONCLUSIONS: ARPIR allows the analysis of RNA-Seq data from groups undergoing different treatment allowing multiple comparisons in a single launch and can be used either for paired-end or single-end analysis. All the required prerequisites can be installed via a configuration script and the analysis can be launched via a graphical interface or by a template script. In addition, ARPIR makes a final tertiary-analysis that includes a Gene Ontology and Pathway analysis. The results can be viewed in an interactive Shiny App and exported in a report (pdf, word or html formats). ARPIR is an efficient and easy-to-use tool for RNA-Seq analysis from quality control to Pathway analysis that allows you to choose between different pipelines. |
format | Online Article Text |
id | pubmed-7751108 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77511082020-12-22 ARPIR: automatic RNA-Seq pipelines with interactive report Spinozzi, Giulio Tini, Valentina Adorni, Alessia Falini, Brunangelo Martelli, Maria Paola BMC Bioinformatics Software BACKGROUND: RNA-Seq is an increasing used methodology to study either coding and non-coding RNA expression. There are many software tools available for each phase of the RNA-Seq analysis and each of them uses different algorithms. Furthermore, the analysis consists of several steps regarding alignment (primary-analysis), quantification, differential analysis (secondary-analysis) and any tertiary-analysis and can therefore be time-consuming to deal with each step separately, in addition to requiring a computer knowledge. For this reason, the development of an automated pipeline that allows the entire analysis to be managed through a single initial command and that is easy to use even for those without computer skills can be useful. Faced with the vast availability of RNA-Seq analysis tools, it is first of all necessary to select a limited number of pipelines to include. For this purpose, we compared eight pipelines obtained by combining the most used tools and for each one we evaluated peak of RAM, time, sensitivity and specificity. RESULTS: The pipeline with shorter times, lower consumption of RAM and higher sensitivity is the one consisting in HISAT2 for alignment, featureCounts for quantification and edgeR for differential analysis. Here, we developed ARPIR, an automated pipeline that recurs by default to the cited pipeline, but it also allows to choose, between different tools, those of the pipelines having the best performances. CONCLUSIONS: ARPIR allows the analysis of RNA-Seq data from groups undergoing different treatment allowing multiple comparisons in a single launch and can be used either for paired-end or single-end analysis. All the required prerequisites can be installed via a configuration script and the analysis can be launched via a graphical interface or by a template script. In addition, ARPIR makes a final tertiary-analysis that includes a Gene Ontology and Pathway analysis. The results can be viewed in an interactive Shiny App and exported in a report (pdf, word or html formats). ARPIR is an efficient and easy-to-use tool for RNA-Seq analysis from quality control to Pathway analysis that allows you to choose between different pipelines. BioMed Central 2020-12-21 /pmc/articles/PMC7751108/ /pubmed/33349239 http://dx.doi.org/10.1186/s12859-020-03846-2 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Spinozzi, Giulio Tini, Valentina Adorni, Alessia Falini, Brunangelo Martelli, Maria Paola ARPIR: automatic RNA-Seq pipelines with interactive report |
title | ARPIR: automatic RNA-Seq pipelines with interactive report |
title_full | ARPIR: automatic RNA-Seq pipelines with interactive report |
title_fullStr | ARPIR: automatic RNA-Seq pipelines with interactive report |
title_full_unstemmed | ARPIR: automatic RNA-Seq pipelines with interactive report |
title_short | ARPIR: automatic RNA-Seq pipelines with interactive report |
title_sort | arpir: automatic rna-seq pipelines with interactive report |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751108/ https://www.ncbi.nlm.nih.gov/pubmed/33349239 http://dx.doi.org/10.1186/s12859-020-03846-2 |
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