Approaches for containerized scientific workflows in cloud environments with applications in life science
- Subject Areas
- Bioinformatics, Computational Biology
- containers, scientific workflow, cloud computing
- © 2018 Spjuth et al.
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2018. Approaches for containerized scientific workflows in cloud environments with applications in life science. PeerJ Preprints 6:e27141v1 https://doi.org/10.7287/peerj.preprints.27141v1
Containers are gaining popularity in life science research as they encompass all dependencies of provisioned tools and simplifies software installations for end users, as well as offering a form of isolation between processes. Scientific workflows are ideal to chain containers into data analysis pipelines to sustain reproducible science. In this manuscript we review the different approaches to use containers inside the workflow tools Nextflow, Galaxy, Pachyderm, Luigi, and SciPipe when deployed in cloud environments. A particular focus is placed on the workflow tool’s interaction with the Kubernetes container orchestration framework.
This is a preprint submission to PeerJ Preprints.