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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 |
Reference manual: | GUniFrac.pdf |
Vignettes: |
Performing differential abundance analysis using ZicoSeq |
Package source: | GUniFrac_1.8.tar.gz |
Windows binaries: | r-devel: GUniFrac_1.8.zip, r-release: GUniFrac_1.8.zip, r-oldrel: GUniFrac_1.8.zip |
macOS binaries: | r-release (arm64): GUniFrac_1.8.tgz, r-oldrel (arm64): GUniFrac_1.8.tgz, r-release (x86_64): GUniFrac_1.8.tgz, r-oldrel (x86_64): GUniFrac_1.8.tgz |
Old sources: | GUniFrac archive |
Reverse imports: | animalcules, chemodiv, LDM, mecoturn, MiRKAT |
Reverse suggests: | microeco |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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