Galaxy and Software Containers: A Recipe for Success

March 11, 2022 3:00 p.m. - 4:00 p.m. ET

Listen to Dr. Enis Afgan’s overview of Galaxy, one of the largest and most widely used open-source platforms for biomedical data science. Dr. Afgan will explore what goes on behind the scenes to make a Galaxy installation function at scale. Specifically, he will discuss:

  • the system architecture of Galaxy and the components it needs to function.
  • how to install Galaxy locally for development and production use cases.
  • the deployment of Galaxy both at and in a FedRAMP-managed environment at AnVIL.
  • how Galaxy is increasingly making use of software containers to ensure consistency and promote software portability.
  • details concerning the Galaxy Helm chart, the latest available model for deploying Galaxy.

This webinar is part of the monthly Containers and Workflows Interest Group (CWIG) webinar series. CWIG brings together data scientists, bioinformaticians, computer scientists, and researchers to learn more about cloud computing and container technologies, workflows, and pipelines that could drive cancer data science.

The webinar series features a variety of presenters from across NIH, industry, and academia. Though cancer research is the focus of the series, unrelated data science and cloud computing topics are still welcome. In the last year, the CWIG webinar speakers have discussed:

  • NIH cloud programs like the Cancer Genomics Cloud (CGC), its fellow NCI Cloud Resources, and NIH Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES).
  • commercial cloud platforms for biomedical data storage and computing.
  • pipelines and tools for deep learning and various omics analysis.
Enis Afgan, Ph.D.

Dr. Afgan is a research scientist in the Schatz Lab at Johns Hopkins University, working on the Galaxy and AnVIL projects. His area of focus has been applying distributed computing techniques to making biomedical computing more accessible. He has been working with cloud computing technologies and software containers to deliver scalable software services for researchers.

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