Abstract
Abstract The Cancer Genomics Cloud (CGC), powered by Seven Bridges, is an NCI-funded platform that streamlines access to large cancer datasets, bioinformatic tools, and cloud computation for cancer researchers. The attributes of the CGC designed to democratize data analysis also make it ideal for training the next generation of data scientists. During the Covid-19 pandemic, it has become clear that remote/virtual learning is of great importance for workforce development, and that reducing barriers to high quality educational resources is critical for many populations. Here we present our best practices for education of bioinformatics using the CGC, taking advantage of both distributed cloud networks and platform features to enhance learning. Our best practices methods are focused on a systematic approach that takes the instructor and students through a typical bioinformatics workflow in their field of research. Briefly, the organizational structure of the CGC, known as “projects,'' contains all aspects of an analysis, including data files, tools, and tool settings. Projects have fine-grained permission settings, which allow the owner to securely share their project for viewing or editing. An instructor can generate an example analysis from start to finish then share an entire project with trainees. Both students and instructors have access to the same data on the cloud, so the teacher can pre-populate the projects with specific files, ensuring the same starting point. All members within the project can communicate, including adding notes directly on the results, allowing students to troubleshoot in real time with the teacher. Instructors can manage costs for the whole class through the CGC’s billing system. The CGC also provides Public Projects for self-guided training, where a researcher can learn by example using the data, tools, and completed tasks within the project, including detailed instructions embedded in markdown language. We have successfully used these methods to train masters students in bioinformatics at Georgetown University for three years, as well as high school students, college students, and current cancer researchers. This approach to virtual learning of bioinformatics can democratize training for the next generation of data scientists. The FAIR practices built into the CGC enables education across all levels of expertise, empowering users to drive cancer research from any stage of their career. Citation Format: Manisha Ray, Sai Lakshmi Subramanian, David Roberson, Zelia Worman, Dennis A. Dean, Soner Koc, Jack DiGiovanna, Brandi Davis-Dusenbery. The Cancer Genomics Cloud enables bioinformatics training in a hybrid educational world [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6393.
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