Single cell RNA-seq analysis
Date: 5 - 12 May 2026
Duration: P1DT16H
Language of instruction: English
Single-cell RNA sequencing (scRNA-seq) has revolutionized transcriptomics by allowing researchers to study gene expression at single-cell resolution. This level of detail is crucial for exploring cellular heterogeneity, discovering novel cell types, and investigating dynamic biological processes such as development and disease progression. You will acquire the skills to analyze and interpret short-read scRNA-seq datasets. Through a combination of theory and hands-on exercises, we will guide you through the complete analysis pipeline from quality control and normalization to clustering, visualization, and differential expression analysis. The training combines theoretical instruction with hands-on activities. On the second day, participants are encouraged to bring their own data sets for practical application and feedback.
Keywords: Artificial Inteligence, omics
Venue: Leuven - Campus Gasthuisberg, Herestraat 49
City: Leuven
Country: Belgium
Postcode: 3000
Learning objectives:
- “ Apply normalization and noise-reduction techniques to enhance signal quality in scRNA-seq datasets”
- “Analyze differential gene expression between experimental conditions to uncover biologically relevant changes”
- “Cluster cells based on gene expression profiles and visualize results using dimensionality reduction methods (UMAP)”
- “Evaluate the effectiveness of preprocessing and clustering methods in revealing biological insights”
- “Identify marker genes for specific clusters to characterize distinct cell populations”
- “Perform quality control and filtering at the cell level to ensure data reliability”
Organizer: VIB (https://ror.org/03xrhmk39)
Event types:
- Workshops and courses
Instructors: 
Janick Mathys
Activity log
