Cargando…
RevEcoR: an R package for the reverse ecology analysis of microbiomes
BACKGROUND: All species live in complex ecosystems. The structure and complexity of a microbial community reflects not only diversity and function, but also the environment in which it occurs. However, traditional ecological methods can only be applied on a small scale and for relatively well-unders...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965897/ https://www.ncbi.nlm.nih.gov/pubmed/27473172 http://dx.doi.org/10.1186/s12859-016-1088-4 |
_version_ | 1782445335051763712 |
---|---|
author | Cao, Yang Wang, Yuanyuan Zheng, Xiaofei Li, Fei Bo, Xiaochen |
author_facet | Cao, Yang Wang, Yuanyuan Zheng, Xiaofei Li, Fei Bo, Xiaochen |
author_sort | Cao, Yang |
collection | PubMed |
description | BACKGROUND: All species live in complex ecosystems. The structure and complexity of a microbial community reflects not only diversity and function, but also the environment in which it occurs. However, traditional ecological methods can only be applied on a small scale and for relatively well-understood biological systems. Recently, a graph-theory-based algorithm called the reverse ecology approach has been developed that can analyze the metabolic networks of all the species in a microbial community, and predict the metabolic interface between species and their environment. RESULTS: Here, we present RevEcoR, an R package and a Shiny Web application that implements the reverse ecology algorithm for determining microbe–microbe interactions in microbial communities. This software allows users to obtain large-scale ecological insights into species’ ecology directly from high-throughput metagenomic data. The software has great potential for facilitating the study of microbiomes. CONCLUSIONS: RevEcoR is open source software for the study of microbial community ecology. The RevEcoR R package is freely available under the GNU General Public License v. 2.0 at http://cran.r-project.org/web/packages/RevEcoR/ with the vignette and typical usage examples, and the interactive Shiny web application is available at http://yiluheihei.shinyapps.io/shiny-RevEcoR, or can be installed locally with the source code accessed from https://github.com/yiluheihei/shiny-RevEcoR. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1088-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4965897 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49658972016-08-02 RevEcoR: an R package for the reverse ecology analysis of microbiomes Cao, Yang Wang, Yuanyuan Zheng, Xiaofei Li, Fei Bo, Xiaochen BMC Bioinformatics Software BACKGROUND: All species live in complex ecosystems. The structure and complexity of a microbial community reflects not only diversity and function, but also the environment in which it occurs. However, traditional ecological methods can only be applied on a small scale and for relatively well-understood biological systems. Recently, a graph-theory-based algorithm called the reverse ecology approach has been developed that can analyze the metabolic networks of all the species in a microbial community, and predict the metabolic interface between species and their environment. RESULTS: Here, we present RevEcoR, an R package and a Shiny Web application that implements the reverse ecology algorithm for determining microbe–microbe interactions in microbial communities. This software allows users to obtain large-scale ecological insights into species’ ecology directly from high-throughput metagenomic data. The software has great potential for facilitating the study of microbiomes. CONCLUSIONS: RevEcoR is open source software for the study of microbial community ecology. The RevEcoR R package is freely available under the GNU General Public License v. 2.0 at http://cran.r-project.org/web/packages/RevEcoR/ with the vignette and typical usage examples, and the interactive Shiny web application is available at http://yiluheihei.shinyapps.io/shiny-RevEcoR, or can be installed locally with the source code accessed from https://github.com/yiluheihei/shiny-RevEcoR. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1088-4) contains supplementary material, which is available to authorized users. BioMed Central 2016-07-29 /pmc/articles/PMC4965897/ /pubmed/27473172 http://dx.doi.org/10.1186/s12859-016-1088-4 Text en © Cao et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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. |
spellingShingle | Software Cao, Yang Wang, Yuanyuan Zheng, Xiaofei Li, Fei Bo, Xiaochen RevEcoR: an R package for the reverse ecology analysis of microbiomes |
title | RevEcoR: an R package for the reverse ecology analysis of microbiomes |
title_full | RevEcoR: an R package for the reverse ecology analysis of microbiomes |
title_fullStr | RevEcoR: an R package for the reverse ecology analysis of microbiomes |
title_full_unstemmed | RevEcoR: an R package for the reverse ecology analysis of microbiomes |
title_short | RevEcoR: an R package for the reverse ecology analysis of microbiomes |
title_sort | revecor: an r package for the reverse ecology analysis of microbiomes |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965897/ https://www.ncbi.nlm.nih.gov/pubmed/27473172 http://dx.doi.org/10.1186/s12859-016-1088-4 |
work_keys_str_mv | AT caoyang revecoranrpackageforthereverseecologyanalysisofmicrobiomes AT wangyuanyuan revecoranrpackageforthereverseecologyanalysisofmicrobiomes AT zhengxiaofei revecoranrpackageforthereverseecologyanalysisofmicrobiomes AT lifei revecoranrpackageforthereverseecologyanalysisofmicrobiomes AT boxiaochen revecoranrpackageforthereverseecologyanalysisofmicrobiomes |