Contents

1 Introduction

The microbiome R package facilitates exploration and analysis of microbiome profiling data, in particular 16S taxonomic profiling.

This vignette provides a brief overview with example data sets from published microbiome profiling studies.

A more comprehensive tutorial is available on-line.

Tools are provided for the manipulation, statistical analysis, and visualization of taxonomic profiling data. In addition to targeted case-control studies, the package facilitates scalable exploration of population cohorts. Whereas sample collections are rapidly accumulating for the human body and other environments, few general-purpose tools for targeted microbiome analysis are available in R. This package supports the independent phyloseq data format and expands the available toolkit in order to facilitate the standardization of the analyses and the development of best practices. See also phylofactor for additional 16S rRNA amplicon analysis tools in R. The aim is to complement the other available packages, but in some cases alternative solutions have been necessary in order to streamline the tools and to improve complementarity.

We welcome feedback, bug reports, and suggestions for new features from the user community via the issue tracker and pull requests. See the Github site for source code and other details. These R tools are released under the Two-clause FreeBSD license.

Kindly cite the work as follows: "Leo Lahti et al. (Bioconductor, 2017-2020). Tools for microbiome analysis in R. Microbiome package version . URL: (http://microbiome.github.io/microbiome)

2 Installation

Loading the package in R (after installation from Bioconductor):

library(microbiome)  

3 Further reading

The on-line tutorial provides many additional tools and examples, with more thorough descriptions. This package and tutorials are work in progress. We welcome feedback, for instance via issue Tracker, pull requests, or via Gitter.

4 Acknowledgements

Thanks to all contributors. Financial support has been provided by Academy of Finland (grants 256950 and 295741), University of Turku.

This work relies heavily on the independent phyloseq package and data structures for R-based microbiome analysis developed by Paul McMurdie and Susan Holmes.