PyHDX is python project which can be used to derive Gibbs free energy from HDX-MS data.

PyHDX web

PyHDX latest documentation

PyHDX on YouTube

Installation of PyHDX with uv:

Create a uv virtual environment, specifying python version 3.11:

$ uv venv -p "3.11"

Then activate environment as instructed by uv, e.g.:

Windows:

$ .venv/Script/activate

Linux/Mac:

$ source .venv/bin/activate

To install PyHDX:

$ uv pip install pyhdx

With web interface extra:

$ uv pip install pyhdx[web]

Conda install (includes web interface extra):

$ conda install pyhdx

Most up-to-date code examples are in the directory pyhdx/templates

To run the web server:

$ pyhdx serve

To add datasets to directly load into PyHDX, configure the database_dir parameter in the config file (default: ~/.hdxms_datasets/datasets), and place hdxms-datasets v0.1.5 (legacy) compatible datasets there.

Please refer to the docs for more details on how to run PyHDX.

The PyHDX web application is currently hosted at: http://pyhdx.jhsmit.org

A test file can be downloaded from here and here (right click, save as).

A beta version might be available at: http://pyhdx-beta.jhsmit.org

Our Analytical Chemistry Publication describing PyHDX can be found here

The latest version (v2) of our biorxiv paper: https://doi.org/10.1101/2020.09.30.320887

Python code for analysis and generation the figures in the paper are here: https://github.com/Jhsmit/PyHDX-paper

HDX MS datasets repository and format: https://github.com/Jhsmit/HDX-MS-datasets

HDXMS datasets python bindings: https://github.com/Jhsmit/hdxms-datasets

Building PyHDX from source:

$ hatch build

Create a new release and distribute to PyPI:

• Create new release on GitHub
• GitHub workflow builds and publishes to PyPI