Snakemake workflow to trim and upload Sars-Cov-2 reads to ENA. This workflow uses ena-upload-cli for upload and updated process_xlsx.py script for metadata table preparation from Galaxys ena_upload tool. Raw reads are adapter-trimmed using bbduk.sh tool and mapped to host/human reference genome using bbmap.sh.
- Download and install miniconda3: https://docs.conda.io/en/latest/miniconda.html.
- Clone this repo and create conda environment
git clone https://github.com/avilab/ena-upload.git
cd ena-upload
conda env create -f workflow/envs/environment.yml
Update files in config
directory:
-
metadata.csv
sample metadata (sample_name, collection_date, experiment id, runs/raw read file names) -
pep.yaml
peppy configuration file to provide full paths to raw reads. -
config.yaml
study wide configuration. -
Check upload rule flags in
Snakefile
, by default, TEST submission (--dev flag in extra parameter) with 'add' action is performed. -
Create
.secret.yml
file with Webin credentials. -
Activate conda environment.
conda activate ena_upload
- Test run:
snakemake -n --use-conda
- Run:
snakemake -j --use-conda
- Hold your breath.
snakemake --dag -d .tests/ | dot -Tsvg > resources/rulegraph.svg