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Basic Structure of Snakemake Pipeline Run !
By Abhi 1605 days ago
/user/snakemake-demo$ ls
config.json data envs scripts slurm-240702.out Snakefile
- data = mock data for the snakefile to use
- Snakefile = name of the snakemake “formula” file
- Note: The default file that snakemake looks for in the current working directory is the
Snakefile. If you would like to override that you can specify it following the-ssnakemake -s snakefile.py
- Note: The default file that snakemake looks for in the current working directory is the
- envs = directory for storing the conda environments that the workflow will use.
- scripts = directory for storing python scripts called by the snakemake formula.
- config.json = json format file with extra parameters for our snakemake file to use.
- cluster.json = json format file with specification for running on the HPC
- samples.txt = file we will use later relating to the config.json file.
Run the snakemake file as a dry run (the example workflow shown above).
- This will build a DAG of the jobs to be run without actually executing them.
snakemake --dry-run
User can execute rules of interest.
snakemake --dry-run allVS.snakemake --dry-run callVS.snakemake --dry-run bwa
Run the snakemake file in order to produce an image of the DAG of jobs to be run.
snakemake --dag | dot -Tsvg > dag.svgORsnakemake --dag | dot -Tsvg > dag.svg
Run the snakemake (this time not as a dry run)
snakemake --use-conda
