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Deep mutational scanning of avian influenza PB2 to comprehensively map adaptation to the human host

Authors: Shirleen Soh, Louise Moncla, Rachel Eguia, Trevor Bedford, Jesse Bloom

Overview

We performed deep mutational scanning of PB2 from avian influenza strain A/Green-winged Teal/Ohio/175/1986 (S009) to comprehensively map the effect of all amino-acid mutations to an avian influenza PB2 on viral replication in different host species.

The computational analyses supporting the manuscript are documented here.

Organization

Analysis notebooks

Analyses are organized by figure. Notebooks for Fig1 through Fig7 need to be run in order.

Running the notebooks

The notebooks are all run in order using the bash script run_notebooks.bash. To run them on the Hutch cluster, use:

sbatch -p largenode -c 14 --mem=300000 --time=48:00:00 run_notebooks.bash

Subdirectories

  • ./scripts/ and ./pymodules/ contains custom scripts and functions used by the analyses.

  • ./data/ contains input data for analysis of deep mutational scanning experiment.

  • ./fastq/ contains the deep mutational scanning and validation sequencing data.

  • ./results/ contains results generated by analysis of deep mutational scanning experiment. Most results are not tracked on GitHub, except for key output files described as follows:

  • ./analyzelibrary/ contains analysis of mutant libraries based on the results from Sanger sequencing some selected clones. Analysis by script analyze_library.py.

  • ./validation/ contains input data and results for validation experiments, as analyzed by Fig4_Validation.ipynb.

  • ./pymol/ contains pymol scripts used to generate annotated structures of PB2, as generated by Fig5_MapDiffSelToStructure.ipynb. Also contains PDB files for S009-PB2 threaded through respective structures.

  • ./compareS009/ contains input data and results for phylogenetic analysis of our chosen avian influenza strain in relation to other influenza strains, as generated by FigS1_compareS009.ipynb.

  • ./paper/ contains figure PDFs used in manuscript figures, as well as supplementary tables submitted with manuscript.

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  • Jupyter Notebook 95.6%
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