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
Packaged: 2026-07-02 08:58:12 UTC; root
Config/pak/sysreqs: cmake make libicu-dev libssl-dev libnode-dev
Repository: https://yushushi.r-universe.dev
Date/Publication: 2021-12-13 07:10:02 UTC
RemoteUrl: https://github.com/cran/aPCoA
RemoteRef: HEAD
RemoteSha: fd03d9f7ee6ca1863f063344ea4e32b76420ca79