Belgium
Analysis of single-cell RNASeq data
Date: 4 - 13 November 2025
Language of instruction: English
Single-cell RNA sequencing (scRNA-seq) has transformed transcriptomics by enabling the study of gene expression at the resolution of individual cells. This level of detail is essential for researchers aiming to understand cellular heterogeneity, identify novel cell types, or explore dynamic biological processes such as development or disease progression. However, analyzing scRNA-seq data requires specialized tools and approaches that differ significantly from bulk RNA-seq workflows. This introductory course is designed for early-stage researchers, including PhD students, postdocs, and technical staff, who are new to single-cell transcriptomics.Participants will gain hands-on experience with the complete analysis pipeline - from quality control and normalization to clustering, visualization, and differential expression analysis. By the end of the course, attendees will be equipped with the foundational skills needed to analyze and interpret scRNA-seq datasets using current best practices independently.
Keywords: omics
Venue: Leuven - Campus Gasthuisberg, Herestraat 49
City: Leuven
Country: Belgium
Postcode: 3000
Learning objectives:
- “Analyze differential gene expression between experimental conditions to uncover biologically relevant changes”
- “Apply normalization and noise reduction techniques to improve signal clarity in scRNA-seq datasets”
- “Cluster cells based on gene expression and visualize the results using dimensionality reduction methods such as UMAP”
- “Evaluate the effectiveness of preprocessing and clustering methods in revealing meaningful biological insights”
- “Identify marker genes for specific cell clusters to characterize distinct cell types”
- “Perform quality control and filtering on the cell levels to ensure high-quality scRNA-seq data”
Organizer: VIB
Event types:
- Workshops and courses
Activity log
