- Tools for Reproducible Science (>4 sessions)
- Basics of R Coding (4 sessions)
- Statistical Modelling, Mixed Models, GLMs in R (6 sessions)
- Bioinformatics with Bash/Python (10 sessions)
Introducing a series of online courses to enable core skills in Biological Data Science. The first course focused in particular on bioinformatics tools using bash and Python and on data visualisation and statistical modelling using R. The current series: Tools for reproducible research focuses on using R for reproducible research, and building reproducible workflows using workspace management tools such as Git and Snakemake.
All teaching is via Zoom video and relies on students coding along an instructor. Each session (currently 1/week) runs for 2 hours with a 30 min break in the middle. Helpers answer questions live on Slack during the session.
Everyone can sign up for free, including, but not limited to, students, academic staff, and non-academic staff. Please register via this form. No need to register again if you have accessed the RStudio server or online Jupyter notebooks during previous sessions.
Video recording of each course and course material can be accessed anytime and everyone is welcome to ask questions on Slack during or after courses.
Organising Committee: Megan McDonald, Thomas Davis, Timothee Bonnet, Jana Sperschneider, Danh-Tai Hoang, Kevin Murray, Saul Newman, Benjamin Schwessinger, Teresa Neeman, Robert Cope, Marcin Adamski, Eric Stone.