README.md

PYP

This folder contains instructions and scripts for processing a time-resolved photactive yellow protein (PYP) dataset. Here, we

1. run careless with a bivariate prior, for many values of the double-Wilson r parameter, and then
2. inspect merging statistics and time-resolved differences.

We start with MTZ files found in ./unmerged_mtzs. These were converted from precognition files provided by Vukica Srajer, for (Dalton et al. Nat. Comm. 2022, https://doi.org/10.1038/s41467-022-35280-8).

To run careless, we use the script careless_runs/slurm-dw-array-grid.sh, which starts a slurm batch array job. This job requires careless_runs/slurm_params.txt, in which we vary the double-Wilson r value across the individual careless runs. To call using slurm:

cd careless_runs
sbatch slurm-dw-array-grid.sh

Many bash scripts require activating a conda environment with careless in it. Please take note that you are activating the right conda environment!

Then, we evaluate the quality of the careless results in two jupyter notebooks, Inspect_Careless_param_grid.ipynb and PYP_diff_map_corr.ipynb. Inspect_Careless_param_grid.ipynb calls the run_ccs.sh script for computing correlation coefficients of careless results. Both of these notebooks also plots figures.

Folders

• unmerged_mtzs: a folder with two unmerged MTZ files containing unmerged reflections from PYP Laue diffraction data. One MTZ contains off data and the other, 2ms after laser irradiation.
• merged_mtzs: output of Inspect_Careless_param_grid.ipynb containing difference maps for each careless run.
• ref: reference MTZ files and pdb files from (Dalton et al. 2022), from files processed by DH using phenix, and PDB entries 1TSO and 2PHY.
• careless_runs: a folder containing a script for running careless as a batch array, as well as the resultant subfolders containing outputs from individual runs of careless.
• pymol: inputs to, and outputs from pymol for visualizing difference maps.
• figures: plot outputs from Jupyter notebooks.