Dates: (online) 3-5 April 2023
This course aims at increasing awareness and introduces strategies on how to improve reproducibility in bioinformatic analyses. Through a mixture of theoretical blocks and hands-on exercises the instructors will guide participants to develop skills to increase reproducibility of bioinformatic analyses and workflows using containers, versioning and virtual environments.
TARGET AUDIENCE AND ASSUMED BACKGROUND
The target audience for this course are graduate students and researchers who work with large datasets. Basic working knowledge of the Linux command line (eg. navigation in the file system, creating files and folders, executing commands) is required and experience with working on remote systems (via ssh) is an advantage. Basic knowledge of a scripting language is also beneficial (eg. python or Perl).
● Basic concepts and techniques for modern reproducible bioinformatics data analyses ● Data organization, documentation and software versioning ● Setting up and working in virtual software environments ● Software containerization strategies and caveats - how to use and build containers ● Knowledge of how to use common workflow management systems