recipe bioconductor-simpleseg

A package to perform simple cell segmentation






Image segmentation is the process of identifying the borders of individual objects (in this case cells) within an image. This allows for the features of cells such as marker expression and morphology to be extracted, stored and analysed. simpleSeg provides functionality for user friendly, watershed based segmentation on multiplexed cellular images in R based on the intensity of user specified protein marker channels. simpleSeg can also be used for the normalization of single cell data obtained from multiple images.

package bioconductor-simpleseg

(downloads) docker_bioconductor-simpleseg



depends bioconductor-biocparallel:


depends bioconductor-cytomapper:


depends bioconductor-ebimage:


depends bioconductor-s4vectors:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-spatstat.geom:

depends r-terra:



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-simpleseg

and update with::

   mamba update bioconductor-simpleseg

To create a new environment, run:

mamba create --name myenvname bioconductor-simpleseg

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

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