This course introduces more advanced tools to increase the reproducibility of data analyses; building upon the Intro to Reproducibility course. GitHub, Docker, Code Review, and GitHub actions are discussed.
This course covers the pitfalls of informatics research and discusses best practices and tools to overcome the challenges of working with and managing multidisciplinary teams. It also covers guidelines to promote diversity and inclusion in your lab and research.
This course covers the basics of creating documentation and tutorials to maximize the usability of informatics tools. It is meant for individuals developing tools for informatics.
This course is designed to help investigators understand more about computing basics, as well as familiarize researchers with various computing platform options.
This course introduces the concepts of reproducibility and replicability in the context of cancer informatics. It is the first course in a two part course on reproducibility. It uses hands-on exercises to demonstrate in practical terms how to increase the reproducibility of data analyses.