recipe bioconductor-rtn

RTN: Reconstruction of Transcriptional regulatory Networks and analysis of regulons






A transcriptional regulatory network (TRN) consists of a collection of transcription factors (TFs) and the regulated target genes. TFs are regulators that recognize specific DNA sequences and guide the expression of the genome, either activating or repressing the expression the target genes. The set of genes controlled by the same TF forms a regulon. This package provides classes and methods for the reconstruction of TRNs and analysis of regulons.

package bioconductor-rtn

(downloads) docker_bioconductor-rtn



depends bioconductor-iranges:


depends bioconductor-limma:


depends bioconductor-minet:


depends bioconductor-reder:


depends bioconductor-s4vectors:


depends bioconductor-summarizedexperiment:


depends bioconductor-viper:


depends r-base:


depends r-car:

depends r-data.table:

depends r-igraph:

depends r-mixtools:

depends r-pheatmap:

depends r-pwr:

depends r-snow:



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-rtn

and update with::

   mamba update bioconductor-rtn

To create a new environment, run:

mamba create --name myenvname bioconductor-rtn

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

Download stats