DESCRIPTION

Package: PACA
Type: Package
Title: Phenotype Aware Components Analysis
Version: 0.5.0
Date: 2022-12-28
Authors@R: person("Aditya", "Gorla", email = "adityagorla@ucla.edu",role = c("aut", "cre"))
Description: Phenotype Aware Components Analysis (PACA) is a contrastive learning approach leveraging canonical 
  correlation analysis to robustly capture weak sources of subphenotypic variation. PACA can be used to define 
  de novo subtypes that are more likely to reflect molecular heterogeneity, especially in challenging cases 
  where the phenotypic heterogeneity may be masked by a myriad of strong unrelated effects in the data.
License: GPL (>= 3)
Imports: 
    Rcpp (>= 1.0.11),
    RcppEigen,
    stats
LinkingTo: Rcpp, RcppEigen
RoxygenNote: 7.2.3
Encoding: UTF-8
URL: https://github.com/adigorla/PACA
BugReports: https://github.com/adigorla/PACA/issues
Suggests: 
    testthat (>= 3.0.0)
Config/testthat/edition: 3