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PEP8 Python 3.12 Shellcheck

About

The pipeline includes the following software and steps:

The snakemake workflow will fail upon error. Once an issue is resolved, it can be restarted and will do so at the point of failure.

Prerequisites

  • Slurm Workload Manager
  • Miniconda 3
  • Snakemake

The pipeline has been tested on a Linux environment using a Slurm Workload Manager.

The project relies on a Kraken 2 database, which is not yet part of this repo so this solution is not currently (standalone) portable.

Main conda environment

Ensure the conda environment exists:

conda activate shivercovid
conda deactivate

If it doesn't exist, create it. E.g:

conda env create -f ./snakemake/environment.yml

Pangolin conda environment

Ensure the conda environment exists:

conda activate pangolin
conda deactivate

If it doesn't exist, create it using the instructions here:

https://github.com/cov-lineages/pangolin#install-pangolin

Running

Manual setup

  1. Create a directory for data processing of the form YYYY-MM-DD_<Batch Name(s)> and navigate to that directory.

  2. Create a samples.txt file containing a list of samples for processing, with one sample per row.

  3. Clone this repo:

    git clone git@github.com:BDI-pathogens/ShiverCovid.git
    
  4. Change directory:

    cd ShiverCovid
    
  5. Replace all <to_be_completed> references in ./snakemake/_config.yaml with information specific to your environment.

  6. Run the preprocessing script:

    ./scripts/preprocessing/setup.sh
    

    You will be prompted for input parameter(s).

  7. Activate the conda environment:

    conda activate shivercovid
    
  8. Execute the Snakemake workflow.

    A script has been provided to submit the job to a Slurm Workload Manager: ./snakemake/submit.sh

    Further information about executing Snakemake can be found in the documentation (https://snakemake.readthedocs.io/en/stable/).

Log files

The location of logs associated with each script will be detailed in the Snakemake output.