Course at Bern, Switzerland: Single-Cell Transcriptomics with R
Single-cell RNA sequencing (scRNAseq) allows researchers to study gene expression at the single cell level. For example, scRNAseq can help to identify expression patterns that differ between conditions within a cell-type. To generate and analyze scRNAseq 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 a scRNAseq experiment. In addition, it will cover the theoretical background of analysis methods with hands-on practical data analysis sessions applied to droplet-based methods.
Application deadline: 06 March 2024
This course is intended for life scientists and bioinformaticians familiar with “Next Generation Sequencing” who want to acquire the necessary skills to analyse scRNA-seq gene expression data.
- Time: 18 - 20 March 2024
- Location: Bern, Switzerland
- Fees: The registration fees for academics are 300 CHF and 1500 CHF for for-profit companies.
At the end of the course, participants will be able to:
- distinguish advantages and pitfalls of scRNAseq
- design their own scRNA-seq experiment
- apply a downstream analysis using R
- Participants should already have a basic knowledge in Next Generation Sequencing (NGS) techniques, or have already followed the “NGS - Quality control, Alignment, Visualisation”.
- Knowledge in RNA sequencing is mandatory.
- Basic knowledge of R is required.
Attendees should have a Wi-Fi enabled computer. An online R and RStudio environment will be provided. However, in case you wish to perform the practical exercises on your own computer, please take a moment to install the following before the course:
- R version > 4.2.
- Latest RStudio version, the free version is perfectly fine.