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Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons
The importance of 16S rRNA gene amplicon profiles for understanding the influence of microbes in a variety of environments coupled with the steep reduction in sequencing costs led to a surge of microbial sequencing projects. The expanding crowd of scientists and clinicians wanting to make use of seq...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5234437/ https://www.ncbi.nlm.nih.gov/pubmed/28097056 http://dx.doi.org/10.7717/peerj.2836 |
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author | Lagkouvardos, Ilias Fischer, Sandra Kumar, Neeraj Clavel, Thomas |
author_facet | Lagkouvardos, Ilias Fischer, Sandra Kumar, Neeraj Clavel, Thomas |
author_sort | Lagkouvardos, Ilias |
collection | PubMed |
description | The importance of 16S rRNA gene amplicon profiles for understanding the influence of microbes in a variety of environments coupled with the steep reduction in sequencing costs led to a surge of microbial sequencing projects. The expanding crowd of scientists and clinicians wanting to make use of sequencing datasets can choose among a range of multipurpose software platforms, the use of which can be intimidating for non-expert users. Among available pipeline options for high-throughput 16S rRNA gene analysis, the R programming language and software environment for statistical computing stands out for its power and increased flexibility, and the possibility to adhere to most recent best practices and to adjust to individual project needs. Here we present the Rhea pipeline, a set of R scripts that encode a series of well-documented choices for the downstream analysis of Operational Taxonomic Units (OTUs) tables, including normalization steps, alpha- and beta-diversity analysis, taxonomic composition, statistical comparisons, and calculation of correlations. Rhea is primarily a straightforward starting point for beginners, but can also be a framework for advanced users who can modify and expand the tool. As the community standards evolve, Rhea will adapt to always represent the current state-of-the-art in microbial profiles analysis in the clear and comprehensive way allowed by the R language. Rhea scripts and documentation are freely available at https://lagkouvardos.github.io/Rhea. |
format | Online Article Text |
id | pubmed-5234437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-52344372017-01-17 Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons Lagkouvardos, Ilias Fischer, Sandra Kumar, Neeraj Clavel, Thomas PeerJ Bioinformatics The importance of 16S rRNA gene amplicon profiles for understanding the influence of microbes in a variety of environments coupled with the steep reduction in sequencing costs led to a surge of microbial sequencing projects. The expanding crowd of scientists and clinicians wanting to make use of sequencing datasets can choose among a range of multipurpose software platforms, the use of which can be intimidating for non-expert users. Among available pipeline options for high-throughput 16S rRNA gene analysis, the R programming language and software environment for statistical computing stands out for its power and increased flexibility, and the possibility to adhere to most recent best practices and to adjust to individual project needs. Here we present the Rhea pipeline, a set of R scripts that encode a series of well-documented choices for the downstream analysis of Operational Taxonomic Units (OTUs) tables, including normalization steps, alpha- and beta-diversity analysis, taxonomic composition, statistical comparisons, and calculation of correlations. Rhea is primarily a straightforward starting point for beginners, but can also be a framework for advanced users who can modify and expand the tool. As the community standards evolve, Rhea will adapt to always represent the current state-of-the-art in microbial profiles analysis in the clear and comprehensive way allowed by the R language. Rhea scripts and documentation are freely available at https://lagkouvardos.github.io/Rhea. PeerJ Inc. 2017-01-11 /pmc/articles/PMC5234437/ /pubmed/28097056 http://dx.doi.org/10.7717/peerj.2836 Text en ©2017 Lagkouvardos et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Lagkouvardos, Ilias Fischer, Sandra Kumar, Neeraj Clavel, Thomas Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons |
title | Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons |
title_full | Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons |
title_fullStr | Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons |
title_full_unstemmed | Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons |
title_short | Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons |
title_sort | rhea: a transparent and modular r pipeline for microbial profiling based on 16s rrna gene amplicons |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5234437/ https://www.ncbi.nlm.nih.gov/pubmed/28097056 http://dx.doi.org/10.7717/peerj.2836 |
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