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

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.

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

Ensure the conda environment exists:

conda activate pangolin
conda deactivate

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

Create a directory for data processing of the form YYYY-MM-DD_<Batch Name(s)> and navigate to that directory.
Create a samples.txt file containing a list of samples for processing, with one sample per row.

Clone this repo:

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

Change directory:
```
cd ShiverCovid
```
Replace all <to_be_completed> references in ./snakemake/_config.yaml with information specific to your environment.
Run the preprocessing script:
```
./scripts/preprocessing/setup.sh
```
You will be prompted for input parameter(s).
Activate the conda environment:
```
conda activate shivercovid
```
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/).

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