Belgium
Analysis of single cell RNASeq data
Date: 23 - 26 September 2025
Single-cell RNASeq provides genome-wide transcriptome data from single cells. The data can be used to unravel heterogeneous cell populations, to discover new cell types and states, and to reconstruct developmental trajectories and fate decisions, all previously masked in bulk transcriptome analyses. Novel methods are required to analyze scRNASeq data, and some of the underlying assumptions for the techniques developed for bulk RNASeq experiments are no longer valid.In this course, we will go through the whole pipeline to analyze short-read scRNASeq data.
Keywords: omics
Venue: Ghent - VIB/UGent FSVM II, Technologiepark 75
City: Zwijnaarde
Country: Belgium
Postcode: 9052
Learning objectives:
- “Analyze differential gene expression between experimental conditions to uncover biologically relevant changes”
- “Apply normalization and noise reduction techniques to enhance signal clarity in single-cell datasets”
- “Cluster cells based on gene expression profiles and visualize the results using dimensionality reduction methods such as UMAP”
- “Identify marker genes for specific cell clusters to characterize distinct cell types or states”
- “Perform quality control and filtering on both gene and cell levels to ensure high-quality scRNA-seq data”
Organizer: VIB
Event types:
- Workshops and courses
Activity log
