1. Approaches for containerized scientific workflows in cloud environments with applications in life science
- Author
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Spjuth, Ola, Capuccini, Marco, Carone, Matteo, Larsson, Anders, Schaal, Wesley, Novella, Jon Ander, Stein, Oliver, Ekmefjord, Morgan, Tommaso, Paolo Di, Floden, Evan, Notredame, Cedric, Moreno, Pablo, Hellander, Andreas, Emami Khoonsari, Payam, Herman, Stephanie, Kultima, Kim, Lampa, Samuel, Spjuth, Ola, Capuccini, Marco, Carone, Matteo, Larsson, Anders, Schaal, Wesley, Novella, Jon Ander, Stein, Oliver, Ekmefjord, Morgan, Tommaso, Paolo Di, Floden, Evan, Notredame, Cedric, Moreno, Pablo, Hellander, Andreas, Emami Khoonsari, Payam, Herman, Stephanie, Kultima, Kim, and Lampa, Samuel
- Abstract
Containers are gaining popularity in life science research as they provide a solution for encompassing dependencies of provisioned tools, simplify software installations for end users and offer a form of isolation between processes. Scientific workflows are ideal for chaining containers into data analysis pipelines to aid in creating reproducible analyses. In this article, we review a number of approaches to using containers as implemented in the workflow tools Nextflow, Galaxy, Pachyderm, Argo, Kubeflow, 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.
- Published
- 2021
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