Clustering

A tool that implements the clustering algorithms from 'mothur' (Schloss PD et al. (2009) ). 'clustur' make use of the cluster() and make.shared() command from 'mothur'. Our cluster() function has five different algorithms implemented: 'OptiClust', 'furthest', 'nearest', 'average', and 'weighted'. 'OptiClust' is an optimized clustering method for Operational Taxonomic Units, and you can learn more here, (Westcott SL, Schloss PD (2017) ). The make.shared() command is always applied at the end of the clustering command. This functionality allows us to generate and create clustering and abundance data efficiently.

Overview

clustur was developed for two main reasons: to allow developers to easily create pipelines with mothur code in R, and to give users a powerful clustering algorithm from mothur without having to download it. Because clustur is built using rcpp, it benefits from the speed of C++ and the usability of R. Additionally, since clustur will be open source, developers can modify are package as needed. This will not only help us continue to create high quality packages, but will allow everyone to take advantage of the foundation that is already built.

Installation

For the official release from CRAN you can use the standard install.packages() function:

# install via cran
install.packages("clustur")
library(clustur)

For the developmental version, you can use the install_github() function from the {devtools} package

# install via github
devtools::install_github("SchlossLab/clustur")
library(clustur)

Getting Started

To get started, look at the “Get started” page.

Contributions

For feature request please visit the issue page in GitHub and use the feature tag. If you would like to contribute pull request are welcomed!