recipe bioconductor-geodiff

Count model based differential expression and normalization on GeoMx RNA data






A series of statistical models using count generating distributions for background modelling, feature and sample QC, normalization and differential expression analysis on GeoMx RNA data. The application of these methods are demonstrated by example data analysis vignette.

package bioconductor-geodiff

(downloads) docker_bioconductor-geodiff



depends bioconductor-biobase:


depends bioconductor-biobase:


depends bioconductor-geomxtools:


depends bioconductor-geomxtools:


depends bioconductor-nanostringnctools:


depends bioconductor-nanostringnctools:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-lme4:

depends r-matrix:

depends r-plyr:

depends r-rcpp:


depends r-rcpparmadillo:

depends r-robust:

depends r-roptim:

depends r-testthat:

depends r-withr:



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-geodiff

and update with::

   mamba update bioconductor-geodiff

To create a new environment, run:

mamba create --name myenvname bioconductor-geodiff

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-geodiff/tags`_ for valid values for ``<tag>``)

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