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Data processing tutorial: insulin

This tutorial demonstrates the essential steps of reciprocal space mapping with mdx2 on a small dataset from cubic insulin.

The tutorial is based on the data processing workshop at the 2022 Erice School on Diffuse Scattering and it accompanies a chapter on data processing in the forthcoming Methods in Enzymology volume "Crystallography of Protein Dynamics”.

To begin, download the jupyter notebooks individually or clone the mdx2 repository. Then, follow the instructions below to download the dataset and create a stand-alone Python environment with all of the software used in the tutorial.

The code is designed to run on a personal computer with ~20 Gb of free disk storage and at least 4 Gb of RAM. A unix-like operating system is assumed (Linux, OSX, or Windows Subsystem for Linux).

Downloading the tutorial dataset

The dataset from insulin is available on Zenodo (https://dx.doi.org/10.5281/zenodo.6536805). First, download insulin_2_1.tar and extract the tar archive. The file will expand to a directory called images with subfolders insulin_2_1, insulin_2_bkg, and metrology. Place images in the same directory as the Jupyter notebooks.

Installing the software

We'll create a single conda environment containing a stand-alone installation of dials, nexpy, jupyter lab, and mdx2. If you already have conda or mamba installed, you can use that. If not, we recommend using micromamba to create the environment.

Install micromamba.

The following will create the conda environment with the minimal dependencies for mdx2:

micromamba create -f https://raw.githubusercontent.com/diff-use/mdx2/main/env.yaml

Answer yes (Y) when prompted.

Next, activate the environment and install dials, nexpy, jupyter lab, and mdx2:

micromamba activate mdx2
micromamba install -c conda-forge dials nexpy jupyterlab
pip install git+https://github.com/diff-use/mdx2

Answer yes (Y) when prompted.

The mdx2 tools should now be available at the command line. Check the version as follows:

mdx2.version

With the mdx2 conda environment active, nexpy can be launched from the command line by typing nexpy. Similarly, Jupyter Lab can be launched by typing jupyter lab. The dials command-line tools are also available. For instance dials.version prints the version information and install location.