Package: ggpca 0.1.2
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>.
Authors:
ggpca_0.1.2.tar.gz
ggpca_0.1.2.zip(r-4.5)ggpca_0.1.2.zip(r-4.4)ggpca_0.1.2.zip(r-4.3)
ggpca_0.1.2.tgz(r-4.4-any)ggpca_0.1.2.tgz(r-4.3-any)
ggpca_0.1.2.tar.gz(r-4.5-noble)ggpca_0.1.2.tar.gz(r-4.4-noble)
ggpca_0.1.2.tgz(r-4.4-emscripten)ggpca_0.1.2.tgz(r-4.3-emscripten)
ggpca.pdf |ggpca.html✨
ggpca/json (API)
# Install 'ggpca' in R: |
install.packages('ggpca', repos = c('https://yaoxiangli.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 days agofrom:6a685a0f50. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 29 2024 |
R-4.5-win | OK | Oct 29 2024 |
R-4.5-linux | OK | Oct 29 2024 |
R-4.4-win | OK | Oct 29 2024 |
R-4.4-mac | OK | Oct 29 2024 |
R-4.3-win | OK | Oct 29 2024 |
R-4.3-mac | OK | Oct 29 2024 |
Dependencies:askpassattemptbase64encbslibcachemclicolorspacecommonmarkconfigcowplotcrayondigestdplyrfansifarverfastmapfontawesomefsgenericsggplot2gluegolemgtableherehtmltoolshttpuvisobandjquerylibjsonlitelabelinglaterlatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigpngpromisesR6rappdirsRColorBrewerRcppRcppEigenRcppTOMLreticulaterlangrprojrootRSpectraRtsnesassscalesshinysourcetoolssystibbletidyselectumaputf8vctrsviridisLitewithrxtableyaml
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Create publication-ready PCA, t-SNE, or UMAP plots | ggpca |
Run the Shiny Application | run_app |