This course was created from this GitHub template.
You can see the rendered course material here: https://hutchdatascience.org/WDL_Workflows_Guide/
If you would like to contribute to this course material, take a look at the OTTR documentation.
"Developing WDL Workflows" shows a bioinformatics workflow developer how to strategically develop and scale up a WDL workflow that is iterative, reproducible, and efficient in terms of time and resource used. This guide is flexible regardless of where the data is, what computing resources are being used, and what software is being used.
This course will teach learners to: how to write an effective WDL task, link multiple WDL tasks together in a workflow, organize variables via structs, scale multiple samples via Arrays, reuse repeated tasks via task aliasing, and configure settings for the execution engine.
If you are encountering any problems with this course, please file a GitHub issue or contact us at {Some email or web address with a contact form}.
All materials in this course are licensed under a Creative Commons Attribution 4.0 International License unless noted otherwise.
