Managing workflow executions with WESkit.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 41734277.
- Also identified by DOI 10.1093/bioinformatics/btag091 and PMC identifier 13032820.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
In biomedical research, managing computational workflows across numerous projects-with varying parameters, tools, and environments-creates major challenges in scalability, reproducibility, and collaboration. Here, we present WESkit, an implementation of the Global Alliance for Genomics and Health (GA4GH) Workflow Execution Service (WES) interface, designed to streamline the execution, monitoring, and documentation of data processing workflows. It addresses the complexities involved in managing numerous executions with varying parameters across diverse research projects. Supporting both Snakemake and Nextflow, the system enables consistent automation and centralized monitoring, which benefits research groups aiming for long-term reproducibility and scalable collaboration. Its suitability for larger teams and service units is further enhanced by seamless integration into cloud environments, contributing to the GA4GH cloud framework. The software WESkit is available under MIT license at the GitLab repository (https://gitlab.com/one-touch-pipeline/weskit). The WESkit main repository is archived at Software Heritage (https://archive.softwareheritage.org/browse/origin/directory/?origin_url=https://gitlab.com/one-touch-pipeline/weskit/api.git) and can be found using "one-touch-pipeline/weskit" term in the search section.
Medical subject headings
- Workflow
- Software
- Genomics
- Computational Biology