Deep mutational scanning of the Nipah virus receptor binding protein (RBP) using a barcoded lentiviral vector

Link to preprint. Study by Brendan Larsen, Teagan McMahon, Jack T. Brown, Zhaoqiang Wang, Caelan E. Radford, James E Crowe Jr., David Veesler, and Jesse Bloom.

For a website that contains additional information about the project, including links to raw data and interactive data visualizations, see https://dms-vep.github.io/Nipah_Malaysia_RBP_DMS/.

Links to raw data

If you are interested in viewing or analyzing the final, filtered deep mutational scanning data, see results/filtered_data/public_filtered/

Information about project

This repo contains data and analyses from deep mutational scanning experiments on the Nipah virus RBP. All experiments were performed on the reference Nipah genome sequenced during the original outbreak in Malaysia NC_002728.1. Thirty two amino acids were removed from the cytoplasmic tail to improve lentivirus titers, and all residues between RBP reference sites 71 and 602 contain every possible single missense mutation. Stop codons were designed to occur at every other position from positions 71 to 234.

Details of repo

The analysis is mostly run by dms-vep-pipeline-3, which is included as a git submodule.

To run the analysis, create the conda environment in dms-vep-pipeline-3/environment.yml, activate it, and run the snakemake pipeline in dms-vep-pipeline-3/Snakefile with: conda activate dms-vep-pipeline-3 snakemake -s dms-vep-pipeline-3/Snakefile -j <n_jobs>

On the Hutch cluster, you can also run with the slurm script run_Hutch_cluster.bash with: sbatch run_Hutch_cluster.bash

The configuration for the analysis is in config.yaml, and additional input data are in ./data/. Additional input data are in ./data/.

Raw experimental and computational data, along with supplemental data for paper are in ./data/custom_analyses_data

The results of running the pipeline are placed in ./results/, only some of which are tracked per the .gitignore file. HTML documentation is created by the pipeline and placed in ./docs/, where it is rendered via GitHub Pages at https://dms-vep.github.io/Nipah_Malaysia_RBP_DMS/

Snakemake file running custom analyses with jupyter notebooks is in custom_rules.smk.

Yaml file containing project specific configurations is nipah_config.yaml

Hosting website with Vitepress

The website hosting the notebooks and interactive plots was built by Vitepress. To modify the directory to serve docs hosted by GitHub Pages, the following steps were taken.

• package.json in root directory contains information about packages needed by vitepress. To generate package-lock.json, run npm install in root.
• In docs/:
  • Contains the markdown files for separate pages.
  • /public contains the raw .html files for the altair plots, jupyter notebooks, and images.
  • .vitepress holds things like website themes and CSS.
  • The file config.mts was modified with base: '/Nipah_Malaysia_RBP_DMS/', to correctly build static website by GitHub Pages.
  • To make sure files are correctly uploaded to GitHub, .gitignore has:
    • node_modules/*
    • !docs/.vitepress/*
    • !docs/public*
  • Added GitHub pages script to .github/workflows/deploy.yml
    • Note: working-directory: docs must be added in two spots in script to make sure the correct directory is built.
  • Modified config.yaml to save all html files to docs/public/ that are built by snakemake pipeline.

To serve the website, run npm run docs:build in root (make sure you have nodejs running in conda environment). Check everything built correctly by running npm run docs:preview. Then simply add and push changes to remote repo.