Teaching Reproducible Data Analysis for HPC Users – The Snakemake Teaching Alliance - Petersen, Malte; Hellmann, Sören Lukas; Böker, Florian; Brand, Fabian; Sharma, Aasish Kumar; Paleico, Martin Leandro; Köster, Johannes; Meesters, Christian (Electronic Communications of the EASST, 2025)
In this article, we introduce the Snakemake HPC Teaching Alliance, a collaborative effort within the Snakemake project aimed at teaching reproducible data analysis to high-performance computing (HPC) users. We address the challenges encountered by researchers new to HPC workflows, aiming to facilitate seamless integration of distributed cluster computing using Snakemake’s batch system support. Our alliance creates educational resources to enable data analysts at every carrier level carrying out reproducible data analysis at large scale, foster HPC accessibility and standardization in bioinformatic workflow solutions aligned with Open Science principles.