Introduction to the microbiome R package

Tools for microbiome analysis; with multiple example data sets from published studies; extending the phyloseq class. The package is in Bioconductor and aims to provide a comprehensive collection of tools and tutorials, with a particular focus on amplicon sequencing data.

Getting started

• Overview (vignette)
  
• Installation
  
• Example data
  
• Data operations (subsetting, transformations etc.)
  
• Cleaning taxonomy table

Microbiome analysis

• Alpha diversity
  
• Beta diversity / Community heterogeneity
  
• Community composition
  
• Core microbiota
  
• Shared core with venn diagram
• Dirichlet Multinomial Mixtures (DMM) for community typing
  
• Dissimilarity-Overlap Analysis (DOC)
  
• Landscapes (population density analysis)
  
• Stability and tipping elements

Visualization and related

• Heatmaps
  
• Ordination (PCA, PCoA, NMDS, RDA etc.)
  
• Regression
  
• Generating output files/figures

Statistical analysis

• Association analysis
  
• Bimodality
  
• Community comparisons (limma, PERMANOVA, mixed models, negative binomial etc)

Tutorial workflows

• Analysis of gut microbiota in 1006 western adults
  
• Univariate tests for two-group comparison

Tips and tricks

• Cleaning taxonomy table
  
• Shared core with Venn diagram

Development

New examples, tutorial pages, and other contributions are welcome. The material can be freely used, modified and distributed under the Two-clause FreeBSD license. For source code, see the Github page.

Contribute

Contributions are welcome:

• Issue Tracker
  
• Pull requests
  
• Subscribe to the mailing list (microbiome-devel@googlegroups.com)
  
• Star us on the Github page

Contibuting new tutorials or examples

We welcome new examples and tutorials to be added in this collection, and will fully acknowledge such contributions.

You can modify one of the existing examples (.html) and make a pull request. Or, you can propose a new tutorial page. The Rmarkdown source code (..html) for all tutorials is available in the Github index.page. Fork the repository, clone it, modify the tutorials, and make a pull request.

Acknowledgements

Kindly cite this work as follows: "Leo Lahti, Sudarshan Shetty et al. (2017). Tools for microbiome analysis in R. Version . URL: http://microbiome.github.com/microbiome. Check also the relevant references listed in the manual page of each function.

The package utilizes tools from a number of other R extensions, including dplyr (Wickham, Francois, Henry, and Müller, 2017), ggplot2 (Wickham, 2009), phyloseq (McMurdie and Holmes, 2013), tidyr (Wickham, 2017), vegan (Oksanen, Blanchet, Friendly, Kindt, Legendre, McGlinn, Minchin, O’Hara, Simpson, Solymos, Stevens, Szoecs, and Wagner, 2017).