Abstract

BackgroundAll 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.ResultsHere, 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.ConclusionsRevEcoR 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 materialThe online version of this article (doi:10.1186/s12859-016-1088-4) contains supplementary material, which is available to authorized users.

Highlights

  • We briefly demonstrate the results from applying RevEcoR to two datasets, a simple dataset containing seven species, and a large-scale dataset consisting of a human gut microbiome

  • Our seven sample oral species metabolic dataset was downloaded from the Integrated Microbial Genomes database (IMG) server; it consists of the following Genomes Online Database (GOLD, http://www.genomesonline.org)

  • We focused on a list of 116 prevalent gut species, whose genome sequences are available in the IMG database and that possess sequence coverage of more than 1 % in at least one metagenomic sample of 124 individuals

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Summary

Results

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
Background
Results and discussion
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