Description: Contains the Markov cluster algorithm (MCL) for identifying clusters in networks and graphs. The algorithm simulates random walks on a (n x n) matrix as the adjacency matrix of a graph. It alternates an expansion step and an inflation step until an equilibrium state is reached.

Title: Simultaneous Estimation of the Regression Coefficients and
Author: T. Tony Cai, Hongzhe Li, Weidong Liu and Jichun Xie
Description: A robust constrained L1 minimization method for estimating
the regression coefficients and a large sparse inverse
covariance matrix (i.e. precision matrix) simultaneoulsy. The

Title: Estimating and Testing Intergenerational Social Mobility Effect
Description: Estimate and test inter-generational social mobility effect on an outcome with cross-sectional or longitudinal data.
Imports: gee, dplyr, lme4, stringr, broomExtra

Imports: survey, gee, dplyr, lme4, stringr, parameters

Title: Bayesian Analysis of Multivariate Counts Data in DNA
Description: 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.

Title: Bayesian analysis of multivariate counts data
Description: This package implements 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