Running Your First Workflow

Hutch Data Core

Updated: March 17, 2023

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If you are working to run a workflow for the first time, you will need to:

  1. Decide where you want the workflow to run
  2. Set up your Nextflow configuration
  3. Pick the workflow you want to run
  4. Set up a run script
  5. Run the workflow

Decide where you want the workflow to run

When running a workflow you have the option to select where the processing will take place. This can either be on your local machine, on the SLURM (gizmo), or in the AWS cloud.

You may select which of these options based on:

  • The size of the workflow - small workflow may run quickly on a local machine;
  • The capacity available to your group in SLURM/gizmo and/or AWS or any associated cost;
  • The location of the input data (see Background on Workflows).

Set up your Nextflow configuration

We recommend that you set up a small “configuration” file which records which type of compute resources should be used to execute a workflow.

For example, if you would like to run a workflow on SLURM, then follow this guide to create a file called nextflow.slurm.config. Similarly, to run a workflow on AWS you may create a file called

The appropriate config file can then be reused to specify compute resources when running any number of workflows by pointing to it in the run script.

Pick the workflow you want to run

Depending on your research goals, you may find a workflow which performs the needed analysis either in our workflow catalog or in the community-developed nf-core workflow catalog.

Depending on the workflow, you may find it useful to use one of the reference databases which have been made available on the shared filesystem (more details here).

If you do not see any useful options available, please don’t hesitate to reach out so that we can find a solution which meets your needs.

Set up a run script

When you have an idea of (a) what workflow you want to run (b) on what computational resources in order to process (c) which particular dataset (input files, parameters, and outputs needed for that workflow); then we recommend that you create a folder where the analysis will be run from (i.e., the working directory for the head node), and create a “run script” in that folder.

The “run script” will contain the full nextflow run ... command, as well as all of the settings and parameters used to run that particular workflow on your particular dataset.

Follow these instructions for setting up that run script.

Run the workflow

Now you are ready to actually run your workflow!

A great workflow to run for the first time which will test that your configuration has been set up correctly is nextflow run hello. This is a very simple “Hello World” workflow which will simply print the word “hello” translated into different languages. While workflows are usually references with some combination of <organization>/<repository> syntax, the hello workflow is just a helpful utility which is bundled into the Nextflow codebase for help with testing.

While the workflow is being executed, you will need to be able to keep the main process running which is responsible for coordinating all of the various tasks. If you are running the workflow from your local computer, just make sure to keep the computer on and connected to the internet (if running on AWS). If running a workflow on the SLURM, a good option is to use sbatch so that the head node itself is run as a SLURM job. Another good approach is to use tmux to keep a session open on a grabbed node for running the head node.

Regardless of where you run the workflow from, you can keep and eye on its progress from anywhere (even your smartphone!) if you make sure to set it up with monitoring in Tower.

Updated: March 17, 2023

Edit this Page via GitHub       Comment by Filing an Issue      Have Questions? Ask them here.