Suite of motif tools, including a motif prediction pipeline for ChIP-seq experiments.
See full GimmeMotifs documentation for detailed installation instructions and usage examples.
For documentation on the development version see here.
The manuscript describing this latest release is available on biorRxiv as a preprint and can be cited as:
GimmeMotifs: an analysis framework for transcription factor motif analysis
Niklas Bruse, Simon J. van Heeringen
bioRxiv (2018) DOI: 10.1101/474403
We need your help!
GimmeMotifs was originally developed for our own needs but we would really like it to be useful to the wider community. However, this also depends on your input. Let us know what you think! What features are missing? Which tutorial would you like to see? What part of the documentation is unclear? Have great ideas for future developments? Maybe you even want to join in developing this software?
If you have not used bioconda before, first set up the necessary channels (in this order!). You only have to do this once.
$ conda config --add channels defaults $ conda config --add channels bioconda $ conda config --add channels conda-forge
You can now install GimmeMotifs with one command:
# Create an environment called gimme with all dependencies $ conda create -n gimme python=3 gimmemotifs # Activate the environment $ conda activate gimme
Python 3 is the required, from version 0.13.0 on GimmeMotifs no longer supports Python 2.
Don't forget to activate the environment with
conda activate gimme whenever you want to use GimmeMotifs.
Predict some motifs:
$ gimme motifs my_peaks.bed -g /data/genomes/hg38/hg38.fa -n my_motifs
Download a genome
The example above assumes that you have the hg38 genome in
GimmeMotifs can also use genomes installed by
You can configure the directory where genomepy stores genomes by editing
To download a genome from UCSC:
$ genomepy install hg38 UCSC --annotation
Now you can specify this genome for GimmeMotifs by name.
$ gimme motifs my_peaks.bed -g hg38 -n my_motifs