recipe bioconductor-hoodscanr

Spatial cellular neighbourhood scanning in R



GPL-3 + file LICENSE



hoodscanR is an user-friendly R package providing functions to assist cellular neighborhood analysis of any spatial transcriptomics data with single-cell resolution. All functions in the package are built based on the SpatialExperiment object, allowing integration into various spatial transcriptomics-related packages from Bioconductor. The package can result in cell-level neighborhood annotation output, along with funtions to perform neighborhood colocalization analysis and neighborhood-based cell clustering.

package bioconductor-hoodscanr

(downloads) docker_bioconductor-hoodscanr



depends bioconductor-complexheatmap:


depends bioconductor-complexheatmap:


depends bioconductor-spatialexperiment:


depends bioconductor-spatialexperiment:


depends bioconductor-summarizedexperiment:


depends bioconductor-summarizedexperiment:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-circlize:

depends r-ggplot2:

depends r-knitr:

depends r-rann:

depends r-rcpp:


depends r-rlang:

depends r-rmarkdown:

depends r-scico:



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-hoodscanr

and update with::

   mamba update bioconductor-hoodscanr

To create a new environment, run:

mamba create --name myenvname bioconductor-hoodscanr

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

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