Package: gcpca 0.0.1
gcpca: Generalized Contrastive Principal Component Analysis
Implements dense and sparse generalized contrastive principal component analysis (gcPCA) with S3 fit objects and methods for prediction, summaries, and plotting. The gcPCA is a hyperparameter-free method for comparing high-dimensional datasets collected under different experimental conditions to reveal low-dimensional patterns enriched in one condition compared to the other. Method details are described in de Oliveira, Garg, Hjerling-Leffler, Batista-Brito, and Sjulson (2025) <doi:10.1371/journal.pcbi.1012747>.
Authors:
gcpca_0.0.1.tar.gz
gcpca_0.0.1.zip(r-4.7)gcpca_0.0.1.zip(r-4.6)gcpca_0.0.1.zip(r-4.5)
gcpca_0.0.1.tgz(r-4.6-any)gcpca_0.0.1.tgz(r-4.5-any)
gcpca_0.0.1.tar.gz(r-4.7-any)gcpca_0.0.1.tar.gz(r-4.6-any)
gcpca_0.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
gcpca/json (API)
| # Install 'gcpca' in R: |
| install.packages('gcpca', repos = c('https://eliezyer.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/sjulsonlab/generalized_contrastive_pca/issues
Last updated from:afbefea2b5. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 88 | ||
| source / vignettes | OK | 150 | ||
| linux-release-x86_64 | OK | 103 | ||
| macos-release-arm64 | OK | 184 | ||
| macos-oldrel-arm64 | OK | 154 | ||
| windows-devel | OK | 63 | ||
| windows-release | OK | 58 | ||
| windows-oldrel | OK | 65 | ||
| wasm-release | OK | 84 |
Exports:gcPCAloadingsscoressparse_gcPCA
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Extract gcPCA loadings | coef.gcPCA coef.sparse_gcPCA |
| Return fitted training scores | fitted.gcPCA |
| Fit a generalized contrastive PCA model | gcPCA |
| Get gcPCA loadings | loadings |
| Plot gcPCA scores | plot.gcPCA |
| Project data with a fitted gcPCA model | predict.gcPCA predict.sparse_gcPCA |
| Print a gcPCA model | print.gcPCA |
| Print a gcPCA summary | print.summary.gcPCA |
| Get gcPCA scores | scores |
| Fit a sparse generalized contrastive PCA model | sparse_gcPCA |
| Summarize a gcPCA model | summary.gcPCA |
