adjclust: Adjacency-Constrained Clustering of a Block-Diagonal Similarity Matrix

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>.

Package details

AuthorChristophe Ambroise [aut], Shubham Chaturvedi [aut], Alia Dehman [aut], Pierre Neuvial [aut, cre] (<https://orcid.org/0000-0003-3584-9998>), Guillem Rigaill [aut], Nathalie Vialaneix [aut] (<https://orcid.org/0000-0003-1156-0639>), Gabriel Hoffman [aut]
Bioconductor views Clustering FeatureExtraction
MaintainerPierre Neuvial <pierre.neuvial@math.univ-toulouse.fr>
LicenseGPL-3
Version0.6.10
URL https://pneuvial.github.io/adjclust/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("adjclust")

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adjclust documentation built on Oct. 8, 2024, 9:07 a.m.