ggpca: Publication-Ready PCA, t-SNE, and UMAP Plots

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>.

Version: 0.1.2
Imports: config (≥ 0.3.2), golem (≥ 0.4.1), shiny (≥ 1.8.1.1), rlang, Rtsne, cowplot, dplyr, ggplot2, umap
Suggests: knitr, tibble, rmarkdown
Published: 2024-10-28
DOI: 10.32614/CRAN.package.ggpca
Author: Yaoxiang Li [cre, aut]
Maintainer: Yaoxiang Li <liyaoxiang at outlook.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: ggpca results

Documentation:

Reference manual: ggpca.pdf
Vignettes: Using ggpca for Publication-Ready Dimensionality Reduction Plots (source, R code)

Downloads:

Package source: ggpca_0.1.2.tar.gz
Windows binaries: r-devel: ggpca_0.1.2.zip, r-release: ggpca_0.1.2.zip, r-oldrel: ggpca_0.1.2.zip
macOS binaries: r-release (arm64): ggpca_0.1.2.tgz, r-oldrel (arm64): ggpca_0.1.2.tgz, r-release (x86_64): ggpca_0.1.2.tgz, r-oldrel (x86_64): ggpca_0.1.2.tgz

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