GUniFrac: 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.
| 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 |
Documentation:
Downloads:
Reverse dependencies:
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