Species richness estimation is an important problem in biodiversity analysis. This package provides methods for total species richness estimation (observed plus unobserved) and a method for modelling total diversity with covariates. breakaway() estimates total (observed plus unobserved) species richness. Microbial diversity datasets are characterized by a large number of rare species and a small number of highly abundant species. The class of models implemented by breakaway() is flexible enough to model both these features. breakaway_nof1() implements a similar procedure however does not require a singleton count. betta() provides a method for modelling total diversity with covariates in a way that accounts for its estimated nature and thus accounts for unobserved taxa, and betta_random() permits random effects modelling.

c(
person("Amy", "Willis", email = "adwillis@uw.edu", role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-2802-4317")),
person("Bryan D", "Martin", role = "aut",
comment = c(ORCID = "0000-0002-8002-5296")),
person("Pauline", "Trinh", role = "aut"),
person("Sarah", "Teichman", role = "aut"),
person("David", "Clausen", role = "aut"),
person("Kathryn", "Barger", role =  "aut"),
person("John", "Bunge", role = "aut")
)
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 species richness, as well as the most commonly used estimates.
ggplot2, graphics, lme4, magrittr, MASS, phyloseq, stats,
tibble, utils
corncob, covr, devtools, dplyr, DT, knitr, openxlsx, plyr,
RCurl, reshape2, R.rsp, remotes, rmarkdown, testthat, tidyverse
Amy Willis [aut, cre] (<https://orcid.org/0000-0002-2802-4317>),
Bryan D Martin [aut] (<https://orcid.org/0000-0002-8002-5296>),
Pauline Trinh [aut],
Sarah Teichman [aut],
David Clausen [aut],
Kathryn Barger [aut],
John Bunge [aut]