Topic: differential expression

Build a statistically rigorous RNA-seq analysis in R and Bioconductor. The workshop develops data import and visualisation skills, hypothesis testing and genomic interval analysis before covering read mapping, count normalisation, differential expression and multiple-testing correction. Practical comparisons include DESeq2, edgeR and limma/voom. The final session interprets functional pathways using overrepresentation and permutation-based gene-set enrichment analysis. Six live online sessions on 2, 3, 5, 6, 9 and 10 November, 15:00–18:00 Europe/Berlin (CET). Fee €530. Basic R programming and

Develop a practical foundation for handling and interpreting next-generation sequencing data. This workshop-style winter school begins with Linux, cloud computing and sequence-quality assessment, then uses containers for reproducible analysis. Exercises cover short- and long-read genome assembly, assembly evaluation, annotation and visualisation, followed by phylogenetics, phylogenomics, RNA-seq processing and differential expression. Examples compare Illumina, Nanopore and PacBio data across biological systems and experimental designs. Live online, 8–12 February, 14:00–20:00 Europe/Berlin (C

This course combines theoretical instruction with practical analysis of transcriptomic and proteomic data. It is designed for biologists and biochemists beginning to use sequencing and mass spectrometry, rather than specialists in either method. Participants study RNA-seq quantification and differential expression, protein identification and quantification, annotation and statistical evaluation. Software training includes SearchGUI, PeptideShaker and DiaNN; Cytoscape is used to integrate measurements and explore complementary information about gene and protein expression. The course connects p