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

Identifies cell population in flow cytometry data

Bioconductor version: Development (3.20)

Samples large data such that spectral clustering is possible while preserving density information in edge weights. More specifically, given a matrix of coordinates as input, SamSPECTRAL first builds the communities to sample the data points. Then, it builds a graph and after weighting the edges by conductance computation, the graph is passed to a classic spectral clustering algorithm to find the spectral clusters. The last stage of SamSPECTRAL is to combine the spectral clusters. The resulting "connected components" estimate biological cell populations in the data. See the vignette for more details on how to use this package, some illustrations, and simple examples.

Author: Habil Zare and Parisa Shooshtari

Maintainer: Habil <zare at>

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


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:

A modified spectral clustering method for clustering Flow Cytometry Data PDF R Script
Reference Manual PDF


biocViews Cancer, CellBiology, Clustering, FlowCytometry, HIV, ImmunoOncology, Software, StemCells
Version 1.59.0
In Bioconductor since BioC 2.6 (R-2.11) (14 years)
License GPL (>= 2)
Depends R (>= 3.3.3)
Imports methods
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Imports Me ddPCRclust
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Source Package SamSPECTRAL_1.59.0.tar.gz
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