This repository contains a Dockerfile and a .devcontainer configuration for an environment with Python 3.11, Clang, and Zsh with plugins plus the mdeq package and necessary dependencies to reproduce the results in that work.
We advise you to use VS Code for this, as it provides a consistent mechanism for starting and working within a Docker container, including the ability to run Jupyter notebooks within the container. See these (somewhat out-of-date) instructions for getting VS Code on the different platforms.
When you have VS Code working, install the official VS Code extensions for Docker and Dev Containers (both authored by Microsoft). Then open the directory containing this file with VS Code. It should trigger a dialog to start the docker container.
- Debian base image.
- Python 3.11 and Clang installed.
- uv and a Python virtual environment.
- Zsh with oh-my-zsh for an enhanced terminal experience.
- Zsh plugins: zsh-autosuggestions and zsh-syntax-highlighting for a more interactive terminal experience.
- accupy python package for accurate floating point arithmetic.
- Eigen C++ library for linear algebra (required for accupy).
- "mdeq==2022.6.30"
- "cogent3[extra]==2025.7.10a5"
When the docker container has started within VS Code, you will find the virtual environment already active in the terminal. So the entering mdeq in the terminal should display the list of sub-commands available.
Entering mdeqasis will show the data prep commands etc.
In the terminal, change into the directory corresponding to the one containing this document
cd MutationDiseqAnalysis
Then execute the script to download and set up both the data sets and the results.
Warning
mdeq_results.zipis ~21GB in size, so it will take some time to download.
python setup_data_results.py