Bridge the "it works on my machine" gap with portable, HPC-ready research environments.

In biomedical research, computational reproducibility is often hindered by complex software dependencies and restrictive high-performance computing (HPC) environments. While Docker is the industry standard for containerization, Apptainer (formerly Singularity) is the gold standard for secure, multi-user research clusters.

This 2-hour, hands-on workshop demystifies containerization for the life sciences. We will move from basic concepts to building a custom, lightweight Linux container specifically for biomedical data science. Using a real-world diabetes analysis pipeline, you will learn how to "freeze" your entire computational environment into a single, portable file that can be shared with collaborators or moved from your laptop to a supercomputer without installation errors.

What you will build: A reproducible analysis pipeline that binds local data into a custom-built container image to produce validated research outputs.

Learning objectives:

By the end of this workshop, participants will be able to:

1. Explain the core differences between containers and virtual machines, and why Apptainer is preferred over Docker in secure HPC environments.
2. Execute fundamental Apptainer CLI commands to pull remote images, explore containers interactively, and run non-interactive commands.
3. Construct an Apptainer Definition File (.def) to build a custom Linux environment containing specific biomedical libraries (e.g., pandas, matplotlib).
4. Analyze a biomedical dataset by binding local data into a containerized pipeline and extracting reproducible, visualized results.
5. Evaluate a research workflow’s reproducibility based on environment documentation, image portability, and data provenance.