Generalized UniFrac Distances, Distance-Based Multivariate Methods and Feature-Based Univariate Methods for Microbiome Data Analysis

A suite of methods for powerful and robust microbiome data analysis including data normalization, data simulation, community-level association testing and differential abundance analysis. It implements generalized UniFrac distances, Geometric Mean of Pairwise Ratios (GMPR) normalization, semiparametric data simulator, distance-based statistical methods, and feature-based statistical methods. The distance-based statistical methods include three extensions of PERMANOVA: (1) PERMANOVA using the Freedman-Lane permutation scheme, (2) PERMANOVA omnibus test using multiple matrices, and (3) analytical approach to approximating PERMANOVA p-value. Feature-based statistical methods include linear model-based methods for differential abundance analysis of zero-inflated high-dimensional compositional data.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


1.4 by Jun Chen, 3 months ago

Browse source code at

Authors: Jun Chen , Xianyang Zhang , Huijuan Zhou

Documentation:   PDF Manual  

Task views: Phylogenetics, Especially Comparative Methods

GPL-3 license

Imports Rcpp, vegan, ggplot2, matrixStats, Matrix, ape, parallel, stats, utils, statmod, rmutil, dirmult, MASS, ggrepel, lmerTest, foreach, modeest

Suggests ade4

Linking to Rcpp

Imported by MiRKAT.

Suggested by microeco.

See at CRAN