recipe bioconductor-spatialdecon

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






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.

package bioconductor-spatialdecon

(downloads) docker_bioconductor-spatialdecon



depends bioconductor-biobase:


depends bioconductor-geomxtools:


depends r-base:


depends r-lognormreg:


depends r-matrix:

depends r-repmis:

depends r-seuratobject:



You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-spatialdecon

and update with::

   mamba update bioconductor-spatialdecon

To create a new environment, run:

mamba create --name myenvname bioconductor-spatialdecon

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-spatialdecon/tags`_ for valid values for ``<tag>``)

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