title: RevEcoR: an R package for the reverse ecology analysis of microbiomes.
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 .
authors.affiliation: Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850, China.|Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Tianjin Institute of Health and Environmental Medicine, Tianjin, 300050, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Cao
authors.affiliation: Department of Basic Courses, Army Officer Academy, Hefei, 230031, China.
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850, China.
authors.forename: Xiaofei
authors.initials: X
authors.lastname: Zheng
authors.affiliation: Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850, China. pittacus@gmail.com.
authors.forename: Fei
authors.initials: F
authors.lastname: Li
authors.affiliation: Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850, China. boxc@bmi.ac.cn.
authors.forename: Xiaochen
authors.initials: X
authors.lastname: Bo
mesh_terms: D000465:Algorithms; D001419:Bacteria / Q000235:genetics; D018407:Bacterial Physiological Phenomena; D004463:Ecology / Q000379:methods; D053858:Metabolic Networks and Pathways; D056186:Metagenomics; D056265:Microbial Interactions; D064307:Microbiota; D012984:Software
keywords: Metabolic network; Microbiome; Reverse ecology