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Deconvolution of mixed cells from spatial and/or bulk gene expression data

Bioconductor version: Release (3.19)

Using spatial or bulk gene expression data, estimates abundance of mixed cell types within each observation. Based on "Advances in mixed cell deconvolution enable quantification of cell types in spatial transcriptomic data", Danaher (2022). Designed for use with the NanoString GeoMx platform, but applicable to any gene expression data.

Author: Maddy Griswold [cre, aut], Patrick Danaher [aut]

Maintainer: Maddy Griswold <mgriswold at>

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


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:

Use of SpatialDecon in a large GeoMx dataset with GeomxTools HTML R Script
Use of SpatialDecon in a small GeoMx dataet HTML R Script
Reference Manual PDF


biocViews FeatureExtraction, GeneExpression, ImmunoOncology, Software, Spatial, Transcriptomics
Version 1.14.0
In Bioconductor since BioC 3.12 (R-4.0) (3.5 years)
License MIT + file LICENSE
Depends R (>= 4.0.0)
Imports grDevices, stats, utils, graphics, SeuratObject, Biobase, GeomxTools, repmis, methods, Matrix, logNormReg (>= 0.4)
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Suggests testthat, knitr, rmarkdown, qpdf, Seurat
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Follow Installation instructions to use this package in your R session.

Source Package SpatialDecon_1.14.0.tar.gz
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macOS Binary (x86_64) SpatialDecon_1.14.0.tgz
macOS Binary (arm64) SpatialDecon_1.14.0.tgz
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Source Repository (Developer Access) git clone
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Old Source Packages for BioC 3.19 Source Archive