Running the workflow

Once your data is set up, perform a dry run of snakemake to see which rules and modules the workflow is configured to run. A dry-run does not actually run the workflow, but determines and prints to screen what will be run based on your configuration file and the current set of results.

-n indicates a dry run.

snakemake --cores 4 --use-conda -n

To run the workflow on 4 cores. Conda will install all necessary packages.

snakemake --cores 4 --use-conda

If using bcl-convert via singularity, you should use:

snakemake --cores 4 --use-singularity --use-conda

If you wish to override using the standard config/config.yaml path, you can provide a config file at the command line as follows.

snakemake --cores 4 --use-conda --use-singularity --configfile myconfig.yaml

If you wish to check that AmpSeeker is configured correctly prior to running it on your dataset, you can run AmpSeeker on the test dataset. To do so, use the following command from the root directory:

snakemake --cores 4 --directory .test/ --use-conda

Running snakemake on a cluster

If you are running snakemake on a cluster which uses queuing systems, you may need to provide some extra parameters at the command line. See the snakemake documentation for more information.

For running the workflow with SLURM, please see the documentation here. Note that native SLURM support requires snakemake version 7.19 or higher.