Abstract
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.
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Cao, Y., Wang, Y., Zheng, X., Li, F., & Bo, X. (2016). RevEcoR: An R package for the reverse ecology analysis of microbiomes. BMC Bioinformatics, 17(1). https://doi.org/10.1186/s12859-016-1088-4
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