RNA-seq Using Galaxy en Français
Date: 11 - 13 August 2025
Biological research generates huge amounts of next-generation sequencing (NGS) data, including RNA-seq. Scientists must have specialized skills and knowledge to effectively collect, analyze, and interpret this data. While most bioinformatics tools require significant programming knowledge to use, which presents a barrier to new bioinformaticians without a computational background, the Galaxy platform allows researchers to perform analyses using a graphical interface. Through lectures and hands-on labs, this 3-day French-language CBW course will provide participants with a comprehensive understanding of the fundamental principles of RNA-seq analysis and the skills to perform this analysis themselves without needing to learn the command line. Each lecture-lab module is designed as a distinct unit and all materials will be available open-access after the workshop concludes. Participants will work through a real case scenario, starting from a publication containing RNA-seq data, moving to quality control, mapping, gene quantification, differential analysis, and functional enrichment using gold standard tools (fastq-dump, FASTQC, fastp, STAR, featurecounts, DESEQ2, g:Profiler). We will also open a Bring your own data session, giving the opportunity to talk with experts about their NGS projects.
City: Montreal
Region: Quebec
Country: Canada
Prerequisites:
You will require your own laptop computer. Minimum requirements: 1024×768 screen resolution, 1.5GHz CPU, 2GB RAM, 10GB free disk space, recent versions of Windows, Mac OS X or Linux (Most computers purchased in the past 3-4 years likely meet these requirements). This workshop requires participants to complete pre-workshop tasks and readings.
Learning objectives:
By the conclusion of the workshop, participants will have practical experience and skills in: Understanding library preparation protocols for RNA-seq and experimental designs Using Galaxy to perform bioinformatics analysis, share content, manage projects, and produce workflow Downloading publicly available data from GEO/SRA Assessing quality of RNA-seq data and perform read trimming Understanding reference genome and transcriptome annotations Mapping RNA-seq data to a reference genome with STAR Visualizing RNA-seq alignments with IGV Estimating gene expression with featurecounts Performing differential expression analysis with DESEQ2 Performing and interpreting principal component analysis (PCA) and hierarchical clustering for outlier detection Performing enrichment analysis with g:Profiler
Capacity: 30
Event types:
- Workshops and courses
Activity log
