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This is the development version of CytoMDS; for the stable release version, see CytoMDS.

Low Dimensions projection of cytometry samples

Bioconductor version: Development (3.20)

This package implements a low dimensional visualization of a set of cytometry samples, in order to visually assess the 'distances' between them. This, in turn, can greatly help the user to identify quality issues like batch effects or outlier samples, and/or check the presence of potential sample clusters that might align with the exeprimental design. The CytoMDS algorithm combines, on the one hand, the concept of Earth Mover's Distance (EMD), a.k.a. Wasserstein metric and, on the other hand, the Multi Dimensional Scaling (MDS) algorithm for the low dimensional projection. Also, the package provides some diagnostic tools for both checking the quality of the MDS projection, as well as tools to help with the interpretation of the axes of the projection.

Author: Philippe Hauchamps [aut, cre] , Laurent Gatto [aut] , Dan Lin [ctb]

Maintainer: Philippe Hauchamps <philippe.hauchamps at>

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


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

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

# The following initializes usage of Bioc devel


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:

Low Dimensional Projection of Cytometry Samples HTML R Script
Reference Manual PDF


biocViews DimensionReduction, FlowCytometry, MultidimensionalScaling, QualityControl, Software, Visualization
Version 1.1.0
In Bioconductor since BioC 3.19 (R-4.4) (< 6 months)
License GPL-3
Depends R (>= 4.3)
Imports methods, stats, rlang, pracma, withr, flowCore, reshape2, ggplot2, ggrepel, ggforce, patchwork, transport, smacof, BiocParallel, CytoPipeline
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Suggests testthat (>= 3.0.0), vdiffr, diffviewer, knitr, rmarkdown, BiocStyle, HDCytoData
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Follow Installation instructions to use this package in your R session.

Source Package CytoMDS_1.1.0.tar.gz
Windows Binary (64-bit only)
macOS Binary (x86_64) CytoMDS_1.1.0.tgz
macOS Binary (arm64) CytoMDS_1.1.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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