MCMC.OTU: Bayesian Analysis of Multivariate Counts Data in DNA Metabarcoding and Ecology
Version 1.0.10

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.

AuthorMikhail V. Matz
Date of publication2016-02-12 00:53:04
MaintainerMikhail V. Matz <matz@utexas.edu>
LicenseGPL-3
Version1.0.10
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("MCMC.OTU")

Getting started

Package overview

Popular man pages

mcmc.otu: Analyzes multivariate counts data using poisson-lognormal...
mcmc.pval: calculates p-value based on Bayesian z-score or MCMC sampling
OTUsummary: Summarizes and plots results of mcmc.otu() function series.
padjustOTU: Adjusts p-values in the OTU summary for multiple comparisons.
panel.cor: accessory function for pairs() to display Pearson...
purgeOutliers: Removes outlier samples and OTUs.
startedLog: prepares OTU counts data for PCA analysis using started-log...
See all...

All man pages Function index File listing

Man pages

getNormalizedOTUdata: Extracts mcmc.otu model predictions
green.data: Symbiodinium sp. ITS2 OTUs from Orbicella franksi and O....
logLin: prepares OTU counts data for PCA analysis using...
mcmc.otu: Analyzes multivariate counts data using poisson-lognormal...
MCMC.OTU-package: Bayesian analysis of multivariate counts data in DNA...
mcmc.pval: calculates p-value based on Bayesian z-score or MCMC sampling
otuByAutocorr: Selects OTUs for which MCMC-based parameter estimates are...
otuStack: Prepares OTU counts data for MCMC model fitting using...
OTUsummary: Summarizes and plots results of mcmc.otu() function series.
padjustOTU: Adjusts p-values in the OTU summary for multiple comparisons.
panel.cor: accessory function for pairs() to display Pearson...
panel.cor.pval: accessory function for pairs() to display pvalue of the...
purgeOutliers: Removes outlier samples and OTUs.
signifOTU: Finds differentially represented OTUs.
startedLog: prepares OTU counts data for PCA analysis using started-log...
summaryPlotOTU: Wrapper function for ggplot2 to make bar and line graphs of...

Functions

MCMC.OTU Man page
MCMC.OTU-package Man page
OTUsummary Man page Source code
getNormalizedOTUdata Man page Source code
green.data Man page
logLin Man page Source code
mcmc.otu Man page Source code
mcmc.pval Man page Source code
otuByAutocorr Man page Source code
otuStack Man page Source code
padjustOTU Man page Source code
panel.cor Man page Source code
panel.cor.pval Man page Source code
purgeOutliers Man page Source code
signifOTU Man page Source code
startedLog Man page Source code
summaryPlotOTU Man page Source code

Files

NAMESPACE
data
data/green.data.rda
R
R/getNormalizedOTUdata.R
R/purgeOutliers.R
R/otuStack.R
R/OTUsummary.R
R/summaryPlotOTU.R
R/padjustOTU.R
R/panel.cor.R
R/panel.cor.pval.R
R/signifOTU.R
R/otuByAutocorr.R
R/startedLog.R
R/mcmc.otu.R
R/MCMC.OTU-internal.R
R/mcmc.pval.R
R/logLin.R
MD5
DESCRIPTION
man
man/mcmc.pval.Rd
man/green.data.Rd
man/purgeOutliers.Rd
man/summaryPlotOTU.Rd
man/signifOTU.Rd
man/getNormalizedOTUdata.Rd
man/logLin.Rd
man/MCMC.OTU-package.Rd
man/panel.cor.Rd
man/otuByAutocorr.Rd
man/panel.cor.pval.Rd
man/padjustOTU.Rd
man/startedLog.Rd
man/mcmc.otu.Rd
man/otuStack.Rd
man/OTUsummary.Rd
MCMC.OTU documentation built on May 19, 2017, 11:47 a.m.

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