Generalized Contrastive Principal Component Analysis R package gcpca version 0.0.1 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>. Software Imports: graphics, stats Suggests: testthat (>= 3.0.0) Eliezyer de Oliveira <eliezyer.deoliveira@gmail.com> Comprehensive R Archive Network (CRAN) Eliezyer de Oliveira [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=gcpca/LICENSE) 2026-04-01 application/tgz https://CRAN.R-project.org/package=gcpca doi:10.32614/CRAN.package.gcpca