GUniFrac: Generalized UniFrac Distances, Distance-Based MultivariateMethods and Feature-Based Univariate Methods for MicrobiomeData 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.
| Version: | 1.9 |
| 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: | 2025-08-25 |
| DOI: | 10.32614/CRAN.package.GUniFrac |
| Author: | Jun Chen [aut, cre], Xianyang Zhang [aut], Lu Yang [aut], Lujun Zhang [aut] |
| Maintainer: | Jun Chen <chen.jun2 at mayo.edu> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| In views: | Phylogenetics |
| CRAN checks: | GUniFrac results |
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