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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "gcpca" in publications use:'
type: software
license: MIT
title: 'gcpca: Generalized Contrastive Principal Component Analysis'
version: 0.0.1
doi: 10.32614/CRAN.package.gcpca
abstract: 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) <https://doi.org/10.1371/journal.pcbi.1012747>.
authors:
- family-names: Oliveira
  given-names: Eliezyer
  name-particle: de
  email: eliezyer.deoliveira@gmail.com
repository: https://eliezyer.r-universe.dev
repository-code: https://github.com/SjulsonLab/generalized_contrastive_PCA
commit: afbefea2b55d19bd533fc70305c5a57e353234a2
url: https://github.com/SjulsonLab/generalized_contrastive_PCA
date-released: '2026-04-01'
contact:
- family-names: Oliveira
  given-names: Eliezyer
  name-particle: de
  email: eliezyer.deoliveira@gmail.com