recipe bioconductor-condiments

Differential Topology, Progression and Differentiation






This package encapsulate many functions to conduct a differential topology analysis. It focuses on analyzing an 'omic dataset with multiple conditions. While the package is mostly geared toward scRNASeq, it does not place any restriction on the actual input format.

package bioconductor-condiments

(downloads) docker_bioconductor-condiments



depends bioconductor-biocparallel:


depends bioconductor-distinct:


depends bioconductor-singlecellexperiment:


depends bioconductor-slingshot:


depends bioconductor-summarizedexperiment:


depends bioconductor-trajectoryutils:


depends r-base:


depends r-dplyr:


depends r-ecume:


depends r-igraph:

depends r-magrittr:

depends r-matrixstats:

depends r-mgcv:

depends r-pbapply:

depends r-rann:



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-condiments

and update with::

   mamba update bioconductor-condiments

To create a new environment, run:

mamba create --name myenvname bioconductor-condiments

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

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