MCMC.OTU: Bayesian Analysis of Multivariate Counts Data in DNA Metabarcoding and Ecology

Poisson-lognormal generalized linear mixed model analysis of multivariate counts data using MCMC, aiming to infer the changes in relative proportions of individual variables. The package was originally designed for sequence-based analysis of microbial communities ("metabarcoding", variables = operational taxonomic units, OTUs), but can be used for other types of multivariate counts, such as in ecological applications (variables = species). The results are summarized and plotted using 'ggplot2' functions. Includes functions to remove sample and variable outliers and reformat counts into normalized log-transformed values for correlation and principal component/coordinate analysis. Walkthrough and examples: http://www.bio.utexas.edu/research/matz_lab/matzlab/Methods_files/walkthroughExample_mcmcOTU_R.txt.

Version: 1.0.10
Depends: MCMCglmm, ggplot2, coda
Published: 2016-02-12
Author: Mikhail V. Matz
Maintainer: Mikhail V. Matz <matz at utexas.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: MCMC.OTU results

Documentation:

Reference manual: MCMC.OTU.pdf

Downloads:

Package source: MCMC.OTU_1.0.10.tar.gz
Windows binaries: r-devel: MCMC.OTU_1.0.10.zip, r-release: MCMC.OTU_1.0.10.zip, r-oldrel: MCMC.OTU_1.0.10.zip
macOS binaries: r-release (arm64): MCMC.OTU_1.0.10.tgz, r-oldrel (arm64): MCMC.OTU_1.0.10.tgz, r-release (x86_64): MCMC.OTU_1.0.10.tgz
Old sources: MCMC.OTU archive

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