22-24  June 2026

Modern genomics produces complex, high-dimensional datasets that require clear and effective visualization for proper interpretation and communication. This course provides a hands-on, practical introduction to creating publication-quality genomics figures using Python. Over three afternoons, participants will develop a personal toolkit of reusable scripts covering a wide range of visualizations, from volcano and Manhattan plots to phylogenetic trees and pangenome graphs.

Participants are expected to be familiar with the Python programming language. A brief introduction to Python and the Python visualization ecosystem will be provided during the first half of the first day to ensure everyone starts with a common foundation.

Throughout the course, participants will work with a combination of general-purpose and genomics-specific Python libraries.

General visualization

• Matplotlib

• Seaborn

• Plotly

Genomics-specific

• PyComplexHeatmap – complex, clustered heatmaps with annotations (Python port of R’s ComplexHeatmap)

• pyCirclize – circos plots for genome-wide relationships

• Toytree – phylogenetic tree drawing and manipulation

• pyMSAviz – multiple sequence alignment visualization

• DashBio (Plotly) – interactive genomics widgets (volcano plots, Manhattan plots, alignment viewers, circos plots)

• pyGenomeTracks – genome browser-style track visualizations

• dna_features_viewer – gene maps and genomic feature diagrams

• JCVI / MCscan – synteny and comparative genomics plots

• UpSetPlot – visualization of complex set intersections

• PyWaffle – waffle charts

• gget – gene and pathway enrichment queries and visualization

• Biopython (Bio.Phylo, Bio.Graphics) – sequence and phylogenetic utilities

Monday — 1:00 to 6:00 PM (Berlin time)

• Introduction to Python and the Python visualization ecosystem

• Volcano plots

• Dimensionality reduction plots (PCA, t-SNE, UMAP)

• Peak visualization

• Pathway and annotation plots

• Heatmaps, waffle plots, and waterfall plots

Tuesday — 1:00 to 6:00 PM (Berlin time)

• Stacked bar plots

• Time series plots

• Multiple sequence alignment visualization

• Manhattan plots

• Genome statistics plots (e.g. genome coverage, gene graphs)

Wednesday — 1:00 to 6:00 PM (Berlin time)

• Phylogenetic trees

• Circos plots

• Venn diagrams and UpSet plots

• Synteny plots

• Ideograms

• Creating an AI agent for making scientific graphs

1 - Introduction to Python for biologists,  ONLINE, 9-12 February

2- Advanced Python for Data Science and Bioinformatics - ONLINE, 23-26 March

3 - Cancer Genomics - ONLINE, 27-29 April

4 - RNAseq for beginners - ONLINE, 19th-28th of May