mdx2 1.0.3

Macromolecular diffuse scattering data reduction

mdx2: macromolecular diffuse scattering data reduction in python

References

Publications describing ando-lab/mdx2:

• Meisburger SP & Ando N. Scaling and merging macromolecular diffuse scattering with mdx2. Acta Cryst. D80, 299-313. DOI
• Meisburger SP & Ando N. Chapter Two - Processing macromolecular diffuse scattering data. In Methods in Enzymology Volume 688, 43-86. DOI, BioRxiv

Mdx2 is based on algorithms and general philosophy of ando-lab/mdx-lib, described here:

• Meisburger SP, Case DA & Ando N. Diffuse X-ray scattering from correlated motions in a protein crystal. Nature Communications 11, 1271 (2020). DOI
• Meisburger SP, Case DA, & Ando N. Robust total X-ray scattering workflow to study correlated motion of proteins in crystals. Nature Communications 14, 1228 (2023). DOI

Examples

• Introductory walkthrough using a small insulin dataset: examples/insulin-tutorial
• Scripts and notebooks to regenerate the figures from Meisburger & Ando, Acta Cryst. D (2024): examples/insulin-multi-crystal.

Versions

Version 1.0.3

• Performance boost for mdx2.import_data using parallel read and write. The data.nxs file contains a virtual dataset linking to neXus files in a subdirectory (datastore/ by default).
• mdx2.reintegrate -- New command-line tool to create fine maps after scaling (single-sweep only: multi-crystal datasets not yet implemented)
• Optional pre-scaling in mdx2.scale to correct anisotropic background
• Improved handling of command-line arguments via dataclass attributes and simple-parsing package
• Updated examples

Version 1.0.2

• Rudimentary Bragg peak integration, in development
• Support for non-reference space group settings
• Bug fixes, including:
  • Symmetry operators now rotate in the correct direction
  • Gracefully skip missing or masked data chunks

Installation

Prerequisites

For a conda-based installation, you'll need micromamba or equivalent.

User install (conda environment)

micromamba create -f https://raw.githubusercontent.com/ando-lab/mdx2/refs/tags/v1.0.3/env.yaml
micromamba activate mdx2
pip install mdx2==1.0.3

You'll probably want these packages too:

micromamba install -c conda-forge dials nexpy jupyterlab xia2

Developer install

See The Diffuse Project's fork for instructions.