Principal Component Analysis (PCA) Tool on Protein Expression Data R package ProteinPCA version 0.1.1 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>. Software Imports: stats, ggplot2, gridExtra Suggests: testthat, MASS Paul Angelo C. Manlapaz <pacmanlapaz@gmail.com> Comprehensive R Archive Network (CRAN) Paul Angelo C. Manlapaz [aut, cre] (ORCID: <https://orcid.org/0000-0002-1203-2064>) GPL-3 2025-08-22 application/tgz https://CRAN.R-project.org/package=ProteinPCA doi:10.32614/CRAN.package.ProteinPCA