HPC-Pipes (Fall 2025)

HPC-Pipes logo

A 2-day course on best practices for setting up, running, and sharing reproducible bioinformatics pipelines and workflows

Join us to learn about the general process of building a robust pipeline (regardless of data type) using workflow languages, environment/package managers, optimized HPC resources, and FAIRly managed data and tools.

The course HPC-Pipes introduces best practices for setting up, running, and sharing reproducible bioinformatics pipelines and workflows. Rather than instruct on the whys and wherefores of using particular tools for a bioinformatics analysis, we will cover the general process of building a robust pipeline (regardless of data type) using workflow languages, environment/package managers, optimized HPC resources, and FAIRly managed data and tools. On course completion, participants will be able to use this knowledge to design their own custom pipelines with tools appropriate for their individual analysis needs.

On course completion, participants will be able to use this knowledge to design their own custom pipelines with tools appropriate for their individual analysis needs.

We strongly recommend taking this course after completing the course HPC-Launch, a single day course which covers theoretical concepts for HPC and RDM in health data science.

Requirements

The workshop is for researchers, professors, and PhD students at SUND who seek to acquire skills in effectively managing data and analyses in bioinformatics. 

Knowledge of R/Python and bash is required, as well as basic understanding of an omics analysis pipeline.

Exercises will be run on the UCloud HPC platform and participants will be expected to build on existing familiarity with bioinformatics tools and the scripting languages bash and R/Python.

Interested?

➡️ If you are an employee, sign up here
➡️ If you are a PhD student, sign up here

Course Disclaimers 

      • The course is free of charge and intended for all KU researchers, and especially PhD students, at SUND
      • A no-show fee will be implemented for registrants who do not attend the course
      • If you are a PhD student and you would like to receive ECTS credits for participating in this course, you must enroll through the PhD school system
      • If you are not a PhD student and sign up via the PhD school registration link, you will be charged for the course
      • Please be advised that course participation via the PhD school happens under the PhD school's terms and conditions which HeaDS has no influence over