recipe bioconductor-motif2site

Detect binding sites from motifs and ChIP-seq experiments, and compare binding sites across conditions






Detect binding sites using motifs IUPAC sequence or bed coordinates and ChIP-seq experiments in bed or bam format. Combine/compare binding sites across experiments, tissues, or conditions. All normalization and differential steps are done using TMM-GLM method. Signal decomposition is done by setting motifs as the centers of the mixture of normal distribution curves.

package bioconductor-motif2site

(downloads) docker_bioconductor-motif2site



depends bioconductor-biocgenerics:


depends bioconductor-biostrings:


depends bioconductor-bsgenome:


depends bioconductor-edger:


depends bioconductor-genomeinfodb:


depends bioconductor-genomicalignments:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-s4vectors:


depends r-base:


depends r-mass:

depends r-mixtools:



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-motif2site

and update with::

   mamba update bioconductor-motif2site

To create a new environment, run:

mamba create --name myenvname bioconductor-motif2site

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-motif2site/tags`_ for valid values for ``<tag>``)

Download stats