Topic: read mapping

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

This practical course introduces next-generation sequencing and the core bioinformatics analyses used with sequencing data. Participants work through quality control and read mapping, learning standard file formats, quality-score encoding and common analysis tools. It is designed for life scientists and computer scientists preparing to analyse NGS data. Familiarity with Galaxy or prior introductory Galaxy training is recommended, and participants need a Galaxy Australia account, their own computer and a reliable internet connection. The online course runs on 4 and 5 November, 13:00–17:00 AEST