The mare R package is an easy-to-use pipeline for microbiota analysis based on 16S-amplicon reads. It takes the raw reads, creates taxonomic tables, visualises the results, and finally identifies organisms significantly associated with variables of interest. For read processing, OTU clustering, and taxonomic annotation the package relies on USEARCH (at least version 8.1.1756_i86osx32, possibly also later versions), which you need to obtain first. Mare has been tested with reads from Illumina HiSeq and MiSeq, 454 pyrosequencing, and Iontorrent, and most functions can be used with microarray data, as well.
For more information see the files mareGuide and mareBackground. To open the files, when you have mare installed, you can run:
browseURL(system.file("mareGuide.pdf", package = "mare"))
browseURL(system.file("mareBackground.pdf", package = "mare"))
Katri Korpela (2016). mare: Microbiota Analysis in R Easily. R package version 1.0. https://github.com/katrikorpela/mare
First install the required packages:
install.packages(c("devtools", "R2admb", "vegan", "sp", "gstat", "Hmisc", "beanplot", "stringr", "MASS", "seqinr", "ggplot2", "reshape2", "qgraph", "gplots", "metacoder"))
If you want to use the graphical user interface, install also the package fgui: install.packages("fgui")
If you want to use the Blast option, install also the package CHNOZS: install.packages("CHNOZS")
If some of the packages cannot be installed, install them manually (see R help pages on how to install packages).
Then continue to run this code to install packages from Bioconductor and R-forge:
devtools::source_url("https://bioconductor.org/biocLite.R")
biocLite(c("Biostrings", "ShortRead","BiocGenerics"))
install.packages("glmmADMB", repos=c("http://glmmadmb.r-forge.r-project.org/repos", getOption("repos")), type="source")
When all packages are installed, you can install mare:
devtools::install_github("katrikorpela/mare")
Blast: Creates a BLAST-based taxonomic table
CAZy: Does carbohydrate enzyme abundance predictions based on the genus table
Clusters: Performs clustering of the bacterial taxa and plots a correlation network
ChangeTest: Tests for differences between groups or associations with covariates in the change of bacterial abundances from one time point to another
CombineProjects: Combines the metadata files and taxonomic tables of two projects that were processed separately.
CommonTaxa: Identifies the most abundant and common taxa in the dataset
CopyFiles: Copies the taxonomic tables and metadata to a new folder for analysis
CorrelationMap: Plots a heatmap of correlations between bacterial taxa and selected variables in the metadata file
CovariatePlot: Plots the selected bacterial taxa against a covariate
CovariateTest: Tests for associations between the bacterial taxa and a covariate
FormatRefDB: Formats a reference database from fasta to UDB-format
GroupPlot: Plots group comparisons
GroupTest: Tests for differences between groups in bacterial abundances
HITChip2Seq: Transforms HITChip data into the same format as sequencing data.
mareGUI: Graphical user interface for mare
Organise: Organises the taxonomic tables based on the metadata file
PathModel: Builds a model for the response variable or for the bacterial taxa, using the bacterial taxa and other variables as explanatory variables in the same model.
PCoA: Pricipal Coordinates Analysis
ProcessReads: Processes the sequencing reads
TaxonomicTable: Creates taxonomic tables
Some reference databases (Silva, and CAZy for carbohydrate utilisation prediction) come with the package to to make getting started easier. To find location of the database, type: filepath <- system.file("extdata", "NameOfTheDatabase", package="mare")
List of databases:
silva_full.fasta (full-length Silva-database)
silva_full.udb (udb-formatted full-length Silva-database)
AA.txt ("Auxiliary Activities" database from CAZy)
CE.txt ("Carbohydrate Esterases" database from CAZy)
GH.txt ("Glycoside Hydrolases" database from CAZy)
GT.txt ("Glycosyl Transferases" database from CAZy)
PL.txt ("Polysaccharide Lyases" database from CAZy)