Advanced Reproducibility in Cancer Informatics (The Course)
This course introduces tools that help enhance reproducibility and replicability in the context of cancer informatics. It uses hands-on exercises to demonstrate in practical terms how to get acquainted with these tools but is by no means meant to be a comprehensive dive into these tools. The course introduces tools and their concepts such as git and GitHub, code review, Docker, and GitHub actions.
This course will demonstrate how to:
- Become familiar with using GitHub in as a part of a analysis project workflow
- Engage in code review steps on GitHub.
- Pull and use an existing Docker image for running an analysis.
- Make data shareable.
- Write a simple Github Actions
- Obtain confidence to learn and apply additional reproducibility tools to an analysis.
Goal of this course:
To equip learners with a deeper knowledge of the capabilities of reproducibility tools and how they can apply to their existing analyses scripts and projects.
What is NOT the goal of this course:
To be a comprehensive tutorial to each of the tools shown.
Each chapter has associated exercises that you are encourage to complete in order to get the full benefit of the course. This course is designed with busy professional learners in mind – who may have to pick up and put down the course when their schedule allows.
- 1 Introduction
- 2 Defining Reproducibility
- 3 Using version control with GitHub
- 4 Providing data
- 5 Engaging in Code Review - as an author
- 6 Engaging in Code Review - as a reviewer
- 7 Launching a Docker image
- 8 Modifying a Docker image
- 9 Automation as a reproducibility tool
- About this Course
- About the Authors
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