Package: adjclust
Maintainer: Pierre Neuvial <pierre.neuvial@math.univ-toulouse.fr>
Authors@R: c(person("Christophe", "Ambroise", role="aut"),
             person("Shubham", "Chaturvedi", role="aut"),
             person("Alia", "Dehman", role="aut"),
             person("Pierre", "Neuvial", role=c("aut", "cre"), 
                 email="pierre.neuvial@math.univ-toulouse.fr"),
             person("Guillem", "Rigaill", role="aut"),
             person("Nathalie", "Vialaneix", role="aut"),             
             person("Gabriel", "Hoffman", role="aut"))
Date: 2022-09-13
Version: 0.6.6
License: GPL-3
Title: Adjacency-Constrained Clustering of a Block-Diagonal Similarity
        Matrix
Description: Implements a constrained version of hierarchical agglomerative 
    clustering, in which each observation is associated to a position, and only 
    adjacent clusters can be merged. Typical application fields in 
    bioinformatics include Genome-Wide Association Studies or Hi-C data 
    analysis, where the similarity between items is a decreasing function of 
    their genomic distance. Taking advantage of this feature, the implemented 
    algorithm is time and memory efficient. This algorithm is described in 
    Ambroise et al (2019) 
    <https://almob.biomedcentral.com/articles/10.1186/s13015-019-0157-4>.
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices, Rcpp (>= 1.0.6), Matrix,
        sparseMatrixStats, methods, utils, capushe
Suggests: knitr, testthat, rmarkdown, rioja, HiTC, snpStats,
        BiocGenerics
biocViews: Clustering, FeatureExtraction
VignetteBuilder: knitr
URL: https://pneuvial.github.io/adjclust/
BugReports: https://github.com/pneuvial/adjclust/issues
RoxygenNote: 7.2.1
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
Language: en-US
NeedsCompilation: yes
Packaged: 2022-09-14 21:40:32 UTC; pneuvial
Author: Christophe Ambroise [aut],
  Shubham Chaturvedi [aut],
  Alia Dehman [aut],
  Pierre Neuvial [aut, cre],
  Guillem Rigaill [aut],
  Nathalie Vialaneix [aut],
  Gabriel Hoffman [aut]
Repository: CRAN
Date/Publication: 2022-09-14 22:00:03 UTC
Built: R 4.1.3; x86_64-w64-mingw32; 2023-04-17 14:34:00 UTC; windows
Archs: i386, x64
