Package: aPCoA 1.3

aPCoA: Covariate Adjusted PCoA Plot

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.

Authors:Yushu Shi

aPCoA_1.3.tar.gz
aPCoA_1.3.zip(r-4.5)aPCoA_1.3.zip(r-4.4)aPCoA_1.3.zip(r-4.3)
aPCoA_1.3.tgz(r-4.4-any)aPCoA_1.3.tgz(r-4.3-any)
aPCoA_1.3.tar.gz(r-4.5-noble)aPCoA_1.3.tar.gz(r-4.4-noble)
aPCoA_1.3.tgz(r-4.4-emscripten)aPCoA_1.3.tgz(r-4.3-emscripten)
aPCoA.pdf |aPCoA.html✨
aPCoA/json (API)

# Install 'aPCoA' in R:
install.packages('aPCoA', repos = c('https://yushushi.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 3 scripts 322 downloads 1 exports 70 dependencies

Last updated 3 years agofrom:fd03d9f7ee. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-winOKNov 13 2024
R-4.5-linuxOKNov 13 2024
R-4.4-winOKNov 13 2024
R-4.4-macOKNov 13 2024
R-4.3-winOKNov 13 2024
R-4.3-macOKNov 13 2024

Exports:aPCoA

Dependencies:abindapebackportsbootbroomcarcarDatacliclustercolorspacecowplotcpp11curlDerivdigestdoBydplyrfansifarverFormulagenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpermutepillarpkgconfigpurrrquantregR6randomcoloRRColorBrewerRcppRcppEigenrlangRtsnescalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8V8vctrsveganviridisLitewithr