recipe bioconductor-memes

motif matching, comparison, and de novo discovery using the MEME Suite






A seamless interface to the MEME Suite family of tools for motif analysis. 'memes' provides data aware utilities for using GRanges objects as entrypoints to motif analysis, data structures for examining & editing motif lists, and novel data visualizations. 'memes' functions and data structures are amenable to both base R and tidyverse workflows.

package bioconductor-memes

(downloads) docker_bioconductor-memes



depends bioconductor-biostrings:


depends bioconductor-genomicranges:


depends bioconductor-universalmotif:


depends r-base:


depends r-cmdfun:


depends r-dplyr:

depends r-ggplot2:

depends r-ggseqlogo:

depends r-magrittr:

depends r-matrixstats:

depends r-patchwork:

depends r-processx:

depends r-purrr:

depends r-readr:

depends r-rlang:

depends r-tibble:

depends r-tidyr:

depends r-usethis:

depends r-xml2:



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-memes

and update with::

   mamba update bioconductor-memes

To create a new environment, run:

mamba create --name myenvname bioconductor-memes

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

Download stats