Analysis of single cell RNASeq data
Analysis of single cell RNASeq data
23 September 2025, 09h30-17h00
26 September 2025, 09h30-17h00
General context
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scRNASeq data, and some of the underlying assumptions for the techniques developed for bulk RNASeq experiments are no longer valid.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.
- Perform quality control and filtering on both gene and cell levels to ensure high-quality scRNA-seq data.
- 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.
- Analyze differential gene expression between experimental conditions to uncover biologically relevant changes.
The content of the course is tailored to the participants' needs.
On the second day, participants can bring their data to analyze.
You should have basic training in R, and we offer a preparatory course that you can follow.
More information can be found on Basic Statistics in R.
Trainers
Janick Mathys
Janick tries to help VIB scientists analyze their data by offering bioinformatics training and support. Next to organizing trainings, creating e-learning courses and teaching statistics, R, Python, Linux, HPC, bulk and single cell RNA-Seq analysis, she consults scientists and develops pipelines for omics analyses. Before joining VIB, she worked as a post-doc at KULeuven, doing research on transcriptomics and transcription regulation. She coordinated the Master of Bioinformatics program of KULeuven and taught the course on Biological Databases.
Thomas Eekhout
Thomas Eekhout started his PhD in 2013 on plant cell cycle regulation in the group of prof. Lieven De Veylder. After obtaining his PhD in 2018 he did a short postdoc in the same group, after which he joined the plant single cell platform of prof. Bert De Rybel in the summer of 2020. Since then, he has loaded and analyzed over two hundred samples from over 20 species for both internal and external groups on different single cell technology platforms.
Program
Analysis via R of publicly available data: quality control
Lunch (provided)
Analysis via R of publicly available data: clustering
Follow up to Seurat pipeline: topics depend on needs of participants
Lunch (provided)
Analysis of own data under guidance of experts from Single Cell Core
Practical info
23 September 2025 - 26 September 2025
Ghent - VIB/UGent FSVM II
Technologiepark 75
9052 Zwijnaarde
Belgium
23 September 2025 - 26 September 2025
Ghent - VIB/UGent FSVM II
From Ghent Sint-Pieters station, you can take a bus to Technologiepark. Please check Routeplanner De Lijn for schedules.
23 September 2025 - 26 September 2025
Ghent - VIB/UGent FSVM II
Looking for a custom cycling route? Try the online cycling route planner to easily and quickly identify the fastest, safest and/or most scenic route to any destination in Ghent.
Cycling route planner
Shared bicycles:
Several providers are active in the area.
Take a look at their platforms:
- Indigo Weel Pro app
- Bluebike
- DOTT
- BOLT eBikes
- Donkey Republic
There are also some public bicycle pumps at the park.
23 September 2025 - 26 September 2025
Ghent - VIB/UGent FSVM II
There is only one entrance to Technologiepark. At the entrance, please take a ticket - Parking is only allowed in regular parking spots (for instance in front of the building) and in the parking tower. Parking alongside the roads or in other places where there is no regular parking is prohibited.