See Dadonaite et al, bioRxiv, DOI 10.1101/2023.11.13.566961 (2023) for the paper describing this study.
This deep mutational scanning study looks at the effects of mutations in BA.2 spike on ACE2 binding using soluble monomeric ACE2 protein.
For documentation of the analysis, see https://dms-vep.github.io/SARS-CoV-2_Omicron_BA.2_spike_ACE2_binding/
Most of the analysis is done by the dms-vep-pipeline-3, which was added as a git submodule to this pipeline via:
git submodule add https://github.com/dms-vep/dms-vep-pipeline-3
This added the file .gitmodules and the submodule dms-vep-pipeline-3, which was then committed to the repo. Note that if you want a specific commit or tag of dms-vep-pipeline-3 or to update to a new commit, follow the steps here, basically:
cd dms-vep-pipeline-3
git checkout <commit>
and then cd ../ back to the top-level directory, and add and commit the updated dms-vep-pipeline-3 submodule.
You can also make changes to the dms-vep-pipeline-3 that you commit back to that repo.
The configuration for the pipeline is in config.yaml and the files in ./data/ referenced therein. To run the pipeline, do:
snakemake -j 8 --use-conda -s dms-vep-pipeline-3/Snakefile
To run on the Hutch cluster via slurm, you can run the file run_Hutch_cluster.bash:
sbatch -c 8 run_Hutch_cluster.bash
The results of running the pipeline are placed in ./results/. Only some of these results are tracked to save space (see .gitignore).
The pipeline builds HTML documentation for the pipeline in ./docs/, which is rendered via GitHub Pages at https://dms-vep.github.io/SARS-CoV-2_Omicron_BA.2_spike_ACE2_affinity/.
The design of the mutant library is contained in ./library_design/. That design is not part of the pipeline but contains code that must be run separately with its own conda environment.