Deep mutational scanning of Lassa virus Josiah strain glycoprotein using a barcoded lentiviral platform

See Carr, Crawford, ..., Bloom for the paper describing this study.

For documentation of the analysis, see https://dms-vep.github.io/LASV_Josiah_GP_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.

Input data

Input data for the pipeline are in ./data/.

Results and documentation

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/LASV_Josiah_GP_DMS/.

Non-pipeline analyses

All other non-pipeline analyses (library construction, phylogeny analysis, virus titers, neutralization assays, etc.) are contained in ./non-pipeline_analyses/. This directory is not part of the pipeline but contains code that must be run separately with its own conda environments.

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