Understanding the drivers of microbial diversity is an important frontier of microbial ecology, and investigating the diversity of samples from microbial ecosystems is a common step in any microbiome analysis.
breakaway is the premier package for statistical
analysis of microbial diversity. breakaway implements the
latest and greatest estimates of richness, as well as the most commonly
used estimates.
DivNet is
a package by the breakaway authors for estimating Shannon
diversity, and other diversity indices. breakaway focuses
on richness while DivNet focuses on Shannon, Simpson, and
other alpha diversities as well as some beta diversity indices. Check it
out!
The R package breakaway implements a number
of different richness estimates. Please cite the following if you use
them:
breakaway() and kemp(): Willis, A. &
Bunge, J. (2015). Estimating diversity via frequency ratios.
Biometrics.betta(): Willis, A., Bunge, J., & Whitman, T.
(2017). Improved detection of changes in species richness in high
diversity microbial communities. JRSS-C.breakaway_nof1(): Willis, A. (2016+). Species richness
estimation with high diversity but spurious singletons. arXiv.objective_bayes_*(): Barger, K. & Bunge, J. (2010).
Objective Bayesian estimation for the number of species. Bayesian
Analysis.You can install breakaway from github by running:
install.packages("devtools")
devtools::install_github("adw96/breakaway")breakaway is actively maintained and continually
expanding and developing its scope! Is there a method you would like to
have implemented in breakaway? Submit a pull request or contact the maintainer!
Maintainer: Amy Willis
Authors: Amy Willis, John Bunge, Bryan Martin, Pauline Trinh, Kathryn Barger, David Clausen and Sarah Teichman.
Do you have a request for us? Let us know! We want folks to use
breakaway and are committed to making it as easy to use as
possible.
Do you have a question? Check out the above documentation list, then shoot us an email or open a Discussion. We receive a lot of emails from users, so we try to answer questions on the Wiki rather than responding to everyone individually.