Skip to content

gcpca

Generalized Contrastive Principal Component Analysis

v0.0.1 · Apr 1, 2026 · MIT + file LICENSE

Description

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>.

Downloads

25

Last 30 days

23694th

25

Last 90 days

25

Last year

CRAN Check Status

10 OK
Show all 10 flavors
Flavor Status
r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK

Check History

OK 6 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Apr 2, 2026

Version History

new 0.0.1 Apr 1, 2026