GUniFrac: Generalized UniFrac Distances, Distance-Based Multivariate Methods and Feature-Based Univariate Methods for Microbiome Data Analysis (original) (raw)

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.

Version: 1.8
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 0.12.13), vegan, ggplot2, matrixStats, Matrix, ape, parallel, stats, utils, statmod, rmutil, dirmult, MASS, ggrepel, foreach, modeest, inline, methods
LinkingTo: Rcpp
Suggests: ade4, knitr, markdown, ggpubr
Published: 2023-09-14
DOI: 10.32614/CRAN.package.GUniFrac
Author: Jun Chen, Xianyang Zhang, Lu Yang, Lujun Zhang
Maintainer: Jun Chen <chen.jun2 at mayo.edu>
License: GPL-3
NeedsCompilation: yes
In views: Phylogenetics
CRAN checks: GUniFrac results

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