The Multiomics Processing (MoP) package is a collection of functions and wrappers used by the Mukamel group for the analysis of transcriptomic and epigenomic data. At the moment MoP is just a collection of functions, but over time it will be packaged into a more user-friendly configuration. The majority of these functions are designed to work with data stored in the loom file format.
- python 3
- loompy
- numpy
- pandas
- scipy
- scikit-learn
- annoy
- MulticoreTSNE
- louvain
- python-igraph
The only way to install MoP is by cloning the GitHub repository. Enter the directory where you would like to download the repository and enter the following commands on the command line:
git clone https://github.com/mukamel-lab/mop.git cd mop python setup.py install
There are some reported issues when running setup.py install related to the installation of some dependencies. If you are using a conda environment the best way to solve these issues is to follow our guide.
Our FAQs has answers to frequently asked questions about using MoP.
For an example notebook showing the processing of methylome (snmC-seq) data please check out this link.
MoP was developed by Wayne Doyle, Fangming Xie, and Ethan Armand in the Mukamel Lab.
We are grateful for support from the Chan-Zuckerberg Initiative and from the NIH BRAIN Initiative U19 Center for Epigenomics of the Mouse Brain Atlas (CEMBA).
