Single-cell RNA sequencing (scRNA-seq) allows researchers to study gene expression at the level of individual cells. This approach can, for example, help to identify different cell populations in a complex sample and describe their expression patterns. To generate and analyse scRNA-seq data, several methods are available, all with their strengths and weaknesses depending on the researchers’ needs. This 3-day course will cover the main technologies as well as the main aspects to consider while designing an scRNA-seq experiment. In particular, it will combine the theoretical background of analytical methods with hands-on data analysis sessions focused on data generated by droplet-based platforms.

By the end of the course, participants will possess the following abilities:
   • Distinguish advantages and pitfalls of scRNA-seq.
   • Design their own scRNA-seq experiment, using common technologies like 10× Genomics.
   • Apply quality control (QC) measures and utilise analysis tools to preprocess scRNA-seq data.
   • Apply normalisation, scaling, dimensionality reduction, integration and clustering on scRNA-seq data using R.
   • Differentiate between cell annotation techniques to identify and characterise cell populations.
   • Use differential gene expression analysis methods on scRNA-seq data to gain biological insights.
   • Select enrichment analysis methods appropriate to the biological question and data.
   • Develop an scRNA-seq data analysis workflow from raw count matrix to differential gene expression with peer support and light guidance.

More information and registration at https://www.elixir-czech.cz/events/course-on-scrna-seq-data-analysis-2025

On behalf of the organisers,

Michal Kolář

—
Laboratory of Genomics and Bioinformatics
Institute of Molecular Genetics of the Czech Academy of Sciences
Videnska 1083
142 20 Prague 4
Czech Republic

Phone +420 241 063 412
Email kolarmi@img.cas.cz <mailto:kolarmi@img.cas.cz>