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ggpca  

Publication-Ready PCA, t-SNE, and UMAP Plots
View on CRAN: Click here


Download and install ggpca package within the R console
Install from CRAN:
install.packages("ggpca")

Install from Github:
library("remotes")
install_github("cran/ggpca")

Install by package version:
library("remotes")
install_version("ggpca", "0.1.3")



Attach the package and use:
library("ggpca")
Maintained by
Yaoxiang Li
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-10-28
Latest Update: 2025-02-04
Description:
Provides tools for creating publication-ready dimensionality reduction plots, including Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP). This package helps visualize high-dimensional data with options for custom labels, density plots, and faceting, using the 'ggplot2' framework Wickham (2016) <doi:10.1007/978-3-319-24277-4>.
How to cite:
Yaoxiang Li (2024). ggpca: Publication-Ready PCA, t-SNE, and UMAP Plots. R package version 0.1.3, https://cran.r-project.org/web/packages/ggpca. Accessed 25 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:43), 0.1.2 (2024-10-28 13:10)
Other packages that cited ggpca R package
View ggpca citation profile
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Complete documentation for ggpca
Functions, R codes and Examples using the ggpca R package
Full ggpca package functions and examples
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