Building Computational Workflows
Overview
This content will guide readers through the basics of WDL computational workflows, why they might be advantageous, and how to best utilize them in the context of the Fred Hutch ecosystem.
Who This Deep Dive Is For
- Anyone who wants to start learning about computational workflows
- People interested in understanding the basics of WDL or the Workflow Description Language ( a coding language used to write computational workflows).
- If you are leading a team that uses (or should use) computational workflows. The broad concepts presented here might be helpful.
Learning Objectives
By the end of this course, you will be able to:
- Understand when and why you should use a computational workflow
- Understand the basic structure of a WDL workflow
- How to executes a workflow on the FH cluster using via PROOF Workbench
- Navigate the WILDS WDL Library to adapt/used WDL workflows
- Customize existing workflows by adding or swapping modules
Course Modules
You can find the presentation for the Winter Quarter (2026) here
| # | Module | Description |
|---|---|---|
| 0 | Pre-Work | What to prepare before diving in |
| 1 | Introduction | Why workflows? Motivation and context |
| 2 | WDL Concepts | Core WDL concepts learned through a Hello World walkthrough |
| 3 | A Real-World Workflow | End-to-end example with ww-sra-salmon from the WILDS WDL Library |
| 4 | Customizing Workflows | Modifying and extending existing pipelines |
| 5 | Running Workflows | Executing workflows with PROOF |
| 6 | Common Pitfalls | Diagnosing errors and fixing common issues |
| 7 | Resources & Next Steps | Where to go from here |
Reference
- Glossary — Key terms and definitions
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