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Clustering Algorithms for Bioconductor

Bioconductor version: Release (3.19)

Wraps common clustering algorithms in an easily extended S4 framework. Backends are implemented for hierarchical, k-means and graph-based clustering. Several utilities are also provided to compare and evaluate clustering results.

Author: Aaron Lun [aut, cre], Stephanie Hicks [ctb], Basil Courbayre [ctb], Tuomas Borman [ctb], Leo Lahti [ctb]

Maintainer: Aaron Lun <infinite.monkeys.with.keyboards at>

Citation (from within R, enter citation("bluster")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

1. Clustering algorithms HTML R Script
2. Clustering diagnostics HTML R Script
Reference Manual PDF


biocViews Clustering, GeneExpression, ImmunoOncology, SingleCell, Software, Transcriptomics
Version 1.14.0
In Bioconductor since BioC 3.12 (R-4.0) (3.5 years)
License GPL-3
Imports stats, methods, utils, cluster, Matrix, Rcpp, igraph, S4Vectors, BiocParallel, BiocNeighbors
System Requirements C++11
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Suggests knitr, rmarkdown, testthat, BiocStyle, dynamicTreeCut, scRNAseq, scuttle, scater, scran, pheatmap, viridis, mbkmeans, kohonen, apcluster, DirichletMultinomial, vegan, fastcluster
Linking To Rcpp
Depends On Me OSCA.advanced, OSCA.basic, OSCA.intro, OSCA.multisample, OSCA.workflows, SingleRBook
Imports Me epiregulon, mia, scDblFinder, scran, Voyager, Canek
Suggests Me batchelor, ChromSCape, concordexR, dittoSeq, mbkmeans, miaViz, MOSim, mumosa, SpatialDDLS
Links To Me
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Follow Installation instructions to use this package in your R session.

Source Package bluster_1.14.0.tar.gz
Windows Binary (64-bit only)
macOS Binary (x86_64) bluster_1.14.0.tgz
macOS Binary (arm64) bluster_1.14.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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