recipe bioconductor-lionessr

Modeling networks for individual samples using LIONESS






LIONESS, or Linear Interpolation to Obtain Network Estimates for Single Samples, can be used to reconstruct single-sample networks ( This code implements the LIONESS equation in the lioness function in R to reconstruct single-sample networks. The default network reconstruction method we use is based on Pearson correlation. However, lionessR can run on any network reconstruction algorithms that returns a complete, weighted adjacency matrix. lionessR works for both unipartite and bipartite networks.

package bioconductor-lionessr

(downloads) docker_bioconductor-lionessr



depends bioconductor-s4vectors:


depends bioconductor-summarizedexperiment:


depends r-base:




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-lionessr

and update with::

   mamba update bioconductor-lionessr

To create a new environment, run:

mamba create --name myenvname bioconductor-lionessr

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

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