Pseudovirus deep mutational scanning of the rabies glycoprotein (G) from the Pasteur strain

Study by Arjun Aditham, Caelan Radford, Caleb Carr, and Jesse Bloom. Please see Aditham et al (2024) for full details about the study.

This repo contains data and analyses from deep mutational scanning experiments on the Rabies glycoprotein (G). All experiments were performed on the Pasteur strain of rabies NC_001542.1.

The deep mutational scan only consists of the ectodomain of Rabies G and few sites flanking the ectodomain. Consistent with the rabies literature, the sites are numbering using the scheme were 1 is assigned to the first site of the ectodomain, not the first site of the protein itself.

For user-friendly links to interactive visualization of the data and key numerical results, see https://dms-vep.org/RABV_Pasteur_G_DMS/.

Organization of this repo

dms-vep-pipeline-3 submodule

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.

Code and configuration

The snakemake pipeline itself is run by dms-vep-pipeline-3/Snakefile which reads its configuration from config.yaml. The conda environment used by the pipeline is that specified in the environment.yml file in dms-vep-pipeline-3.

Data

Input data utilized by the pipeline are located in ./data/.

Additional Data

Plasmid, Primer, antibody sequences alongside library synthesis quality reports are contained in ./Additional_Data/. A README file in that directory explains contents.

Results and documentation

The results of running the pipeline are placed in ./results/. Due to space, only some results are tracked. For those that are not, see the .gitignore document.

The pipeline builds HTML documentation for the pipeline in ./docs/, and a nicely formatted set is put in ./homepage/. These docs are rendered for viewing at https://dms-vep.org/RABV_Pasteur_G_DMS/ as stated above.

Non-pipeline analyses

Additional analyses run outside the core pipeline are in ./non-pipeline_analyses/, and are described by README files within that subdirectory:

• ./non-pipeline_analyses/Additional_Notebooks contains notebooks and raw for most of the figures in the manuscript.
• ./non-pipeline_analyses/RABV_nextstrain contains notebooks and raw for most of the figures in the manuscript.

Running the pipeline

To run the pipeline, build the conda environment dms-vep-pipeline-3 in the environment.yml file of dms-vep-pipeline-3, activate it, and run snakemake, such as:

conda activate dms-vep-pipeline-3
snakemake -j 32 --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 32 run_Hutch_cluster.bash

Note that if you are just cloning this repo and want to re-run it without having to obtain and re-parse all the FASTQ files, you can use the pre-existing barcode count files by setting the use_precomputed_barcode_counts key in config.yaml to true. If you are running the pipeline not on the Fred Hutch server with the FASTQs, this is the recommended approach (otherwise you will need to download the FASTQs and re-assign the paths in barcode_runs).