Analysis and Visualization Tools for Microbial Community Data

An approach to the visualization, analysis, and interpretation of (microbial) community composition data, especially those originating from amplicon sequencing. Analysis techniques include constrained and unconstrained ordination and visualizing taxonomic abundances and spatial patterns, among others. Methods intended to assist bioinformaticians and ecologists in selecting read trimming by quality scores and preprocessing/denoising of datasets are also provided.


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Overview

theseus provides functions to assist in the analysis, visualization, and interpretation of community composition data, especially those originating from amplicon sequencing.

Relevant Software and Literature

Callahan, Sankaran, Fukuyama, McMurdie, and Holmes (2017) Bioconductor Workflow for Microbiome Data Analysis: from raw reads to community analyses McMurdie and Holmes (2013) phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data Oksanen,Blanchet, Friendly, Kindt, Legendre, McGlinn, Minchin, O'Hara, Simpson, Solymos, Stevens, Szoecs, and Wagner (2017) vegan: Community Ecology Package

Installation

install.packages('theseus')
 
# To install the developmental version via Github:
# install.packages('devtools')
devtools::install_github('sw1/theseus',build_vignettes=TRUE)

Development

For future feature requests or suggestions, request an issue:

https://github.com/sw1/theseus/issues

News

theseus 0.1.0

  • First release.

Reference manual

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install.packages("theseus")

0.1.0 by Stephen Woloszynek, a year ago


http://github.com/EESI/theseus


Report a bug at http://github.com/EESI/theseus/issues


Browse source code at https://github.com/cran/theseus


Authors: Jacob Price [aut] , Stephen Woloszynek [cre, aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports dplyr, ggplot2, gridExtra, magrittr, parallel, phyloseq, ShortRead, splancs, tidyverse, tidyr, vegan, viridis

Suggests covr, knitr, rmarkdown, testthat


See at CRAN