Enrich2 is a general software tool for processing, analyzing, and visualizing data from deep mutational scanning experiments. For more information or to cite Enrich2, please refer to A statistical framework for analyzing deep mutational scanning data.
Enrich2 documentation is available on Read the Docs.
An example dataset is available at the Enrich2-Example GitHub repository.
Enrich2 runs on Python 2.7 and requires the following packages:
- NumPy version 1.10.4 or higher
- SciPy version 0.16.0 or higher
- pandas version 0.18 or higher
- PyTables version 3.2.0 or higher
- Statsmodels version 0.6.1 or higher
- matplotlib version 1.4.3 or higher
The configuration GUI requires Tkinter. Building a local copy of the documentation requires Sphinx.
We recommend using a scientific Python distribution such as Anaconda to install and manage dependencies. A Conda environment file is included with the documentation.
To install Enrich2 using Anaconda (or Miniconda), git clone or download and unzip the Enrich2 code. From the Enrich2 directory, create the environment, activate the environment, and install Enrich2:
conda env create -f docs/_static/enrich2_env.yml
conda activate enrich2
python setup.py install
You should now be able to launch the Enrich2 graphical user interface by typing enrich_gui or the command line interface by typing enrich_cmd.
Please use the GitHub Issue Tracker to file bug reports or request features.
Enrich2 was written by Alan F Rubin.