3 Reproducible Research

A key goal of our Biology program at UBC’s Okanagan campus is to foster appreciation for reproducible research, and to equip students (and professors) with skills that will help them undertake reproducible research themselves.

In first year you may have learned from the Biology program’s introductory Open Science learning modules that reproducible research studies are not as common as one might assume. (If you did not cover that material, do so now). One key reason for this is insufficient documentation of all the steps taken along the research workflow. Moreover, conducting reproducible research is extremely challenging - more than most scientists appreciate. See, for example, an incredible, recent case concerning ageing experiments with C. elegans here.

In the BIOL202 lectures you’ll learn more about the various causes of irreproducible research, and about the practices that can help promote reproducibility. In this lab component of the course, you’ll learn the basics of how to achieve an acceptable level of computational reproducibility (complete computational reproducibility is actually pretty tricky, but we’ll get close).

Learning Outcomes

Upon successful completion, students will be able to:
1. Implement a computationally reproducible workflow using R, RStudio, and R Markdown
2. Organize and manage data and project files using versioned, structured formats
3. Create clean, analysis-ready datasets in .csv or .rds formats
4. Use R Markdown to document and explain all analysis steps and results