Package: ProteinPCA 0.1.0

ProteinPCA: Principal Component Analysis (PCA) Tool on Protein Expression Data

Analysis of protein expression data can be done through Principal Component Analysis (PCA), and this R package is designed to streamline the analysis. This package enables users to perform PCA and it generates biplot and scree plot for advanced graphical visualization. Optionally, it supports grouping/clustering visualization with PCA loadings and confidence ellipses. With this R package, researchers can quickly explore complex protein datasets, interpret variance contributions, and visualize sample clustering through intuitive biplots. For more details, see Jolliffe (2001) <doi:10.1007/b98835>, Gabriel (1971) <doi:10.1093/biomet/58.3.453>, Zhang et al. (2024) <doi:10.1038/s41467-024-53239-9>, and Anandan et al. (2022) <doi:10.1038/s41598-022-07781-5>.

Authors:Paul Angelo C. Manlapaz [aut, cre]

ProteinPCA_0.1.0.tar.gz
ProteinPCA_0.1.0.zip(r-4.7)ProteinPCA_0.1.0.zip(r-4.6)ProteinPCA_0.1.0.zip(r-4.5)
ProteinPCA_0.1.0.tgz(r-4.6-any)ProteinPCA_0.1.0.tgz(r-4.5-any)
ProteinPCA_0.1.0.tar.gz(r-4.7-any)ProteinPCA_0.1.0.tar.gz(r-4.6-any)
ProteinPCA_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
ProteinPCA/json (API)

# Install 'ProteinPCA' in R:
install.packages('ProteinPCA', repos = c('https://piey27.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/piey27/proteinpca/issues

On CRAN:

Conda:

2.00 score 1 stars 459 downloads 1 exports 18 dependencies

Last updated from:3ecd7337a7. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK122
source / vignettesOK159
linux-release-x86_64OK126
macos-release-arm64OK75
macos-oldrel-arm64OK83
windows-develOK85
windows-releaseOK71
windows-oldrelOK68
wasm-releaseOK100

Exports:pca_analysis

Dependencies:clicpp11farverggplot2gluegridExtragtableisobandlabelinglifecycleR6RColorBrewerrlangS7scalesvctrsviridisLitewithr