recipe bioconductor-kinswingr

KinSwingR: network-based kinase activity prediction






KinSwingR integrates phosphosite data derived from mass-spectrometry data and kinase-substrate predictions to predict kinase activity. Several functions allow the user to build PWM models of kinase-subtrates, statistically infer PWM:substrate matches, and integrate these data to infer kinase activity.

package bioconductor-kinswingr

(downloads) docker_bioconductor-kinswingr



depends bioconductor-biocparallel:


depends r-base:


depends r-data.table:

depends r-sqldf:



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-kinswingr

and update with::

   mamba update bioconductor-kinswingr

To create a new environment, run:

mamba create --name myenvname bioconductor-kinswingr

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

Download stats