Bayesian Analysis of Multivariate Counts Data in DNA Metabarcoding and Ecology
Extracts mcmc.otu model predictions
prepares OTU counts data for PCA analysis using log-linear-hybrid tran...
Bayesian analysis of multivariate counts data in DNA metabarcoding and...
Analyzes multivariate counts data using poisson-lognormal mixed model
calculates p-value based on Bayesian z-score or MCMC sampling
Selects OTUs for which MCMC-based parameter estimates are reliable.
Prepares OTU counts data for MCMC model fitting using mcmc.otu().
Summarizes and plots results of mcmc.otu() function series.
Adjusts p-values in the OTU summary for multiple comparisons.
accessory function for pairs() to display pvalue of the Pearson correl...
accessory function for pairs() to display Pearson correlations
Removes outlier samples and OTUs.
Finds differentially represented OTUs.
prepares OTU counts data for PCA analysis using started-log transform
Wrapper function for ggplot2 to make bar and line graphs of mcmc.otu()...
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.