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>.

Version:	0.1.1
Imports:	stats, ggplot2, gridExtra
Suggests:	testthat, MASS
Published:	2025-08-22
DOI:	10.32614/CRAN.package.ProteinPCA
Author:	Paul Angelo C. Manlapaz [aut, cre]
Maintainer:	Paul Angelo C. Manlapaz <pacmanlapaz at gmail.com>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	ProteinPCA results

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