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: |
0.1.0 |
| Imports: |
stats, ggplot2, gridExtra |
| Suggests: |
testthat |
| Published: |
2025-04-12 |
| 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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