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) , Gabriel (1971) , Zhang et al. (2024) , and Anandan et al. (2022) .


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("ProteinPCA")

0.1.1 by Paul Angelo C. Manlapaz, a year ago


Browse source code at https://github.com/cran/ProteinPCA


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


Documentation:   PDF Manual  


GPL-3 license


Imports stats, ggplot2, gridExtra

Suggests testthat, MASS


See at CRAN