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adjclust: Adjacency-Constrained Clustering of a Block-Diagonal Similarity Matrix (original) (raw)

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) <doi:10.1186/s13015-019-0157-4>.

Version: 0.6.10
Depends: R (≥ 4.0.0)
Imports: stats, graphics, grDevices, Rcpp (≥ 1.0.6), Matrix, sparseMatrixStats, methods, utils, capushe, ggplot2, dendextend, rlang
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, testthat, rmarkdown, rioja, HiTC, snpStats, BiocGenerics
Published: 2024-10-08
DOI: 10.32614/CRAN.package.adjclust
Author: Christophe Ambroise [aut], Shubham Chaturvedi [aut], Alia Dehman [aut], Pierre Neuvial ORCID iD [aut, cre], Guillem Rigaill [aut], Nathalie VialaneixORCID iD [aut], Gabriel Hoffman [aut]
Maintainer: Pierre Neuvial <pierre.neuvial at math.univ-toulouse.fr>
BugReports: https://github.com/pneuvial/adjclust/issues
License: GPL-3
URL: https://pneuvial.github.io/adjclust/
NeedsCompilation: yes
Language: en-US
Citation: adjclust citation info
Materials: README NEWS
In views: Omics
CRAN checks: adjclust results

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