Single-Cell Transcriptomics with R

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Overview

In contrast to bulk RNA sequencing, single-cell RNA sequencing (scRNA-seq) allows researchers to study gene expression profiles at a single cell resolution. This enables the discovery of tissue specific cell subpopulations and markers, and has revolutionized the way we can use gene expression data to answer biological questions. This 3-day course will cover the most-used technologies to generate scRNA-seq data, as well as the main aspects to consider while designing a scRNAseq experiment. Participants will get hands-on experience in scRNA-seq data analysis by means of extensive practical analysis sessions with R. The training materials for this course are in its dedicated GitHub page. GitHub page.

Audience

This course is intended for life scientists familiar with next generation sequencing analysis methods who want to acquire the necessary skills to analyze scRNA-seq data.

Learning objectives

At the end of the course, participants will be able to:

• Explain the characteristics of the most-used methods to generate transcriptomic data at the single-cell level, with a focus on 10x genomics.
• Perform quality control at different steps of the analysis of single cell transcriptomic data.
• Use dimensionality reduction (PCA, t-SNE, UMAP) and clustering algorithms for visualization and downstream analyses
• Apply best practices for translating single cell transcriptomic data into biological knowledge by using cell annotation, differential gene expression analysis and trajectory analysis

Knowledge / competencies prerequired (Mandatory)

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 a plus. A basic knowledge of the R statistical software is required. Test your R skills with the quiz here, before registering.

Technical requirements

Please check the required installation detailed here, before the start of the course.

Program

The program of this course can be found in its dedicated GitHub page.

Application

The registration fees for academics are 180 CHF and 900 CHF for for-profit companies. While participants are registered on a first come, first served basis, exceptions may be made to ensure diversity and equity, which may increase the time before your registration is confirmed.

You will be informed by email of your registration confirmation. Upon reception of the confirmation email, participants will be asked to confirm attendance by paying the fees within 5 days.

Applications will close once the places will be filled. Deadline for registration and free-of-charge cancellation is set to 20/06/2022. Cancellation after this date will not be reimbursed. Please note that participation in SIB courses is subject to our general conditions.

Venue and Time

This course will take place at the University of Bern.

It will start at 9:15 and end around 17:15.

Precise information will be provided to the participants in due time.

Additional information

Coordination: Valeria Di Cola

We will recommend 0.75 ECTS credits for this course (given a passed exam at the end of the course).

You are welcome to register to the SIB courses mailing list to be informed of all future courses and workshops, as well as all important deadlines using the form here.

Please note that participation in SIB courses is subject to our general conditions.

SIB abides by the ELIXIR Code of Conduct. Participants of SIB courses are also required to abide by the same code.

For more information, please contact training@sib.swiss.