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Using self-organizing maps for visualization and interpretation of cytometry data

Bioconductor version: Release (3.19)

FlowSOM offers visualization options for cytometry data, by using Self-Organizing Map clustering and Minimal Spanning Trees.

Author: Sofie Van Gassen [aut, cre], Artuur Couckuyt [aut], Katrien Quintelier [aut], Annelies Emmaneel [aut], Britt Callebaut [aut], Yvan Saeys [aut]

Maintainer: Sofie Van Gassen <sofie.vangassen at>

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


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:

FlowSOM PDF R Script
Reference Manual PDF


biocViews CellBasedAssays, CellBiology, Clustering, FlowCytometry, Software, Visualization
Version 2.12.0
In Bioconductor since BioC 3.1 (R-3.2) (9 years)
License GPL (>= 2)
Depends R (>= 4.0), igraph
Imports stats, utils, colorRamps, ConsensusClusterPlus, dplyr, flowCore, ggforce, ggnewscale, ggplot2, ggpubr, grDevices, magrittr, methods, rlang, Rtsne, tidyr, BiocGenerics, XML
System Requirements
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Suggests BiocStyle, testthat, CytoML, flowWorkspace, ggrepel, scattermore, pheatmap, ggpointdensity
Linking To
Depends On Me
Imports Me CATALYST, diffcyt
Suggests Me HDCytoData
Links To Me
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package FlowSOM_2.12.0.tar.gz
Windows Binary
macOS Binary (x86_64) FlowSOM_2.12.0.tgz
macOS Binary (arm64) FlowSOM_2.12.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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