Trying your first Gitpod environment

You can run Gitpod with any nf-core pipeline repository.

For example, for nf-core RNA-seq pipeline, simply click the green Gitpod button or add the Gitpod prefix before the git URL (instead of https://github.com/nf-core/rnaseq, type https://gitpod.io/#https://github.com/nf-core/rnaseq).

Once Gitpod has loaded, including the container with all the tools we need, we can go to the terminal and type the following to start the nf-core workflow:

nextflow run nf-core/rnaseq \
    -profile test,docker \
    --outdir my_result
nextflow run nf-core/rnaseq \
    -profile test,docker \
    --outdir my_result

This should run the test data through nf-core rnaseq, using docker with your results in the folder: my_result. This will take some time to complete.

Using this Gitpod method makes it easy to run and test nf-core pipelines quickly, but it lacks the parallelization required to run real datasets.

Testing your module with pytest

With DSL2, much of pipeline writing is spent writing reusable modules. If you enter the Gitpod environment for modules, you can run the pytest function in order to debug a particular module.

You can learn more about pytest in this nf-core bytesize talk.

Once you are in the environment, try running an example pytest for an existing module:

PROFILE=docker pytest --tag <module_name> --symlink --keep-workflow-wd --git-aware
PROFILE=docker pytest --tag <module_name> --symlink --keep-workflow-wd --git-aware