recipe bioconductor-imcrtools

Methods for imaging mass cytometry data analysis






This R package supports the handling and analysis of imaging mass cytometry and other highly multiplexed imaging data. The main functionality includes reading in single-cell data after image segmentation and measurement, data formatting to perform channel spillover correction and a number of spatial analysis approaches. First, cell-cell interactions are detected via spatial graph construction; these graphs can be visualized with cells representing nodes and interactions representing edges. Furthermore, per cell, its direct neighbours are summarized to allow spatial clustering. Per image/grouping level, interactions between types of cells are counted, averaged and compared against random permutations. In that way, types of cells that interact more (attraction) or less (avoidance) frequently than expected by chance are detected.

package bioconductor-imcrtools

(downloads) docker_bioconductor-imcrtools



depends bioconductor-biocneighbors:


depends bioconductor-biocparallel:


depends bioconductor-cytomapper:


depends bioconductor-ebimage:


depends bioconductor-matrixgenerics:


depends bioconductor-s4vectors:


depends bioconductor-scuttle:


depends bioconductor-singlecellexperiment:


depends bioconductor-spatialexperiment:


depends bioconductor-summarizedexperiment:


depends r-abind:

depends r-base:


depends r-concaveman:

depends r-data.table:

depends r-distances:

depends r-dplyr:

depends r-dt:

depends r-ggplot2:

depends r-ggraph:

depends r-igraph:

depends r-magrittr:

depends r-pheatmap:

depends r-readr:

depends r-rtriangle:

depends r-sf:

depends r-stringr:

depends r-tidygraph:

depends r-tidyselect:

depends r-viridis:

depends r-vroom:



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-imcrtools

and update with::

   mamba update bioconductor-imcrtools

To create a new environment, run:

mamba create --name myenvname bioconductor-imcrtools

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

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