Package: aPCoA
Type: Package
Title: Covariate Adjusted PCoA Plot
Version: 1.3
Date: 2021-12-12
Author: Yushu Shi
Maintainer: Yushu Shi <shiyushu2006@gmail.com>
Description: In fields such as ecology, microbiology, and genomics, non-Euclidean distances are widely applied to describe pairwise dissimilarity between samples. Given these pairwise distances, principal coordinates analysis (PCoA) is commonly used to construct a visualization of the data. However, confounding covariates can make patterns related to the scientific question of interest difficult to observe. We provide 'aPCoA' as an easy-to-use tool to improve data visualization in this context, enabling enhanced presentation of the effects of interest. Details are described in Yushu Shi, Liangliang Zhang, Kim-Anh Do, Christine Peterson and Robert Jenq (2020) Bioinformatics, Volume 36, Issue 13, 4099-4101.
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: vegan, randomcoloR, ape, car, cluster
NeedsCompilation: no
Repository: CRAN
Packaged: 2021-12-12 20:47:35 UTC; ys8wp
Date/Publication: 2021-12-13 08:10:02 UTC
Built: R 4.6.0; ; 2026-04-25 14:06:54 UTC; unix
