Author: Patricio S. La Rosa, Elena Deych, Berkley Shands, William D.
Depends: R (>= 2.13.0), MCMCpack, dirmult
Description: This package provides several functions to perform formal
hypothesis testing, and power and sample size calculations for
distribution is proposed for modeling the species abundance
distributions of human microbiota (ranked bacterial taxa

distribution is proposed to model species abundance and ranked

Imports: MASS, gplots, doParallel, foreach, parallel
Description: Using Dirichlet-Multinomial distribution to provide several functions for formal hypothesis testing, power and sample size calculations for human microbiome experiments.

Author: Patricio S. La Rosa, Elena Deych, Sharina Carter, Berkley Shands, William D. Shannon
Imports: ggplot2, stats, foreach, doParallel, MASS, vegan, gplots,
rpart, rpart.plot, parallel, graphics, lattice

Author: Patricio S. La Rosa, Elena Deych, Sharina Carter, Berkley Shands, Dake Yang, William D. Shannon

Title: Statistical Object Oriented Data Analysis of RDP-based Taxonomic
trees from Human Microbiome Data: Modeling, Visualization, and
Suggests: doSMP, foreach, multicore, doMC
Description: In this package, we introduce Object Oriented Data Analysis (OODA) methods to analyze Human Microbiome taxonomic trees directly. We provide tools to model, compare, and visualize populations of taxonomic tree objects. In particular, using a unimodal probability measure in the set of trees, we provide procedures to compute the MLE of the central tree and the LRT statistics for comparing the distributions of two metagenomic populations. Our procedures have been developed to support parallel computations for comparing two groups.

Description: In this package, we introduce Object Oriented Data
Analysis (OODA) methods to analyze Human Microbiome taxonomic
trees directly. We provide tools to model, compare, and
visualize populations of taxonomic tree objects. In particular,
using a unimodal probability measure in the set of trees, we
provide procedures to compute the MLE of the central tree and
the LRT statistics for comparing the distributions of two
metagenomic populations. Our procedures have been developed to
support parallel computations for comparing two groups.