Practical, discussion-heavy course on creating reproducible, publication-ready figures for genomics and broader biological research. We focus on adapting existing R/Python scripts, annotating plots thoughtfully, and polishing outputs with lightweight graphic tools. Expect small-group exercises (3–4 people), frequent instructor feedback, and encouragement to leverage AI copilots (e.g., ChatGPT, Gemini) responsibly for coding help.
- Audience: PhD students, postdocs, and early-career researchers in biology, bioinformatics, or related life sciences fields with basic programming experience.
- Schedule: 18–20 November 2025, 10:00–17:00 CET (online via Zoom, 6 hours per day including breaks).
- Bring: Laptop with R + Python (or Colab), access to your preferred AI assistant, and Inkscape (free vector editor).
Key theoretical points and live examples are also summarized in the shared slides: Google Slides deck.
| Day | Theme | Primary Tools | Folder / Notes |
|---|---|---|---|
| Day 1 – Foundations & Basic Plotting | Python data wrangling, scatter/bar/violin/box plots, annotations, TSV vs CSV hygiene. | Python (pandas, matplotlib), Google Colab option. | first_day/ (coming soon). |
| Day 2 – Advanced Visualization Techniques (Part 1) | Dimensionality reduction (PCA) and related genomics plots. | R, tidyverse. | second_day_part1/ (coming soon). |
| Day 2 – Advanced Visualization Techniques (Part 2 – Heatmaps) | ComplexHeatmap workflows, annotations, and publication-ready layouts (materials in this repo section). | R, ComplexHeatmap, Circlize. | second_day_part2/ (heatmap module in this repo). |
| Day 3 – From Plot to Publication | Final polish: DPI, file formats, multi-panel figure assembly, Inkscape editing tips. | R, Inkscape, optional Python touch-ups. | Materials forthcoming (third_day/). |