recipe bioconductor-cellmixs

Evaluate Cellspecific Mixing



GPL (>=2)



CellMixS provides metrics and functions to evaluate batch effects, data integration and batch effect correction in single cell trancriptome data with single cell resolution. Results can be visualized and summarised on different levels, e.g. on cell, celltype or dataset level.

package bioconductor-cellmixs

(downloads) docker_bioconductor-cellmixs



depends bioconductor-biocgenerics:


depends bioconductor-biocneighbors:


depends bioconductor-biocparallel:


depends bioconductor-scater:


depends bioconductor-singlecellexperiment:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-cowplot:

depends r-dplyr:

depends r-ggplot2:

depends r-ggridges:

depends r-ksamples:

depends r-magrittr:

depends r-purrr:

depends r-tidyr:

depends r-viridis:



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-cellmixs

and update with::

   mamba update bioconductor-cellmixs

To create a new environment, run:

mamba create --name myenvname bioconductor-cellmixs

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

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