Package: hierBipartite
Type: Package
Title: Bipartite Graph-Based Hierarchical Clustering
Version: 0.0.2
Authors@R: c(person("Calvin", "Chi", email = "calvin.chi@berkeley.edu", role = c("aut", "cre", "cph")),
           person("Woojoo", "Lee", role = c("ctb")),
           person("Donghwan", "Lee", role = c("ctb")),
           person("Youngjo", "Lee", role = c("ctb")),
           person("Yudi", "Pawitan", role = c("ctb")))
Maintainer: Calvin Chi <calvin.chi@berkeley.edu>
Description: 
    Bipartite graph-based hierarchical clustering, developed for pharmacogenomic 
    datasets and datasets sharing the same data structure. The goal is to 
    construct a hierarchical clustering of groups of samples based on 
    association patterns between two sets of variables. In the context of
    pharmacogenomic datasets, the samples are cell lines, and the two sets of 
    variables are typically expression levels and drug sensitivity values. 
    For this method, sparse canonical correlation analysis from 
    Lee, W., Lee, D., Lee, Y. and Pawitan, Y. (2011) <doi:10.2202/1544-6115.1638> 
    is first applied to extract association patterns for each group of samples. 
    Then, a nuclear norm-based dissimilarity measure is used to construct a 
    dissimilarity matrix between groups based on the extracted associations. 
    Finally, hierarchical clustering is applied.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: parallel, magrittr, irlba
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-12 15:02:07 UTC; calvinchi
Author: Calvin Chi [aut, cre, cph],
  Woojoo Lee [ctb],
  Donghwan Lee [ctb],
  Youngjo Lee [ctb],
  Yudi Pawitan [ctb]
Repository: CRAN
Date/Publication: 2021-02-16 09:40:02 UTC
Built: R 4.6.0; ; 2026-02-14 03:26:15 UTC; windows
