25 October 2024
Application deadline:
11 October 2024
Cancellation deadline:
11 October 2024
Lea Taylor, Stephanie Talker & Lorenzo Raeli
Omics data analysis
Academic: 100 CHF
For-profit: 500 CHF
0.25 ECTS credits

No future instance of this course is planned yet


Recent advances in omics technologies allow us to grasp the complexity of the immune system, but data analysis and interpretation remain highly challenging. Data scientists require a basic understanding of immunology and associated methods to collaborate effectively and efficiently in immunological research projects.

In this one-day course we aim to close knowledge gaps and promote a general understanding of the immune system. We will focus on immune cells and their functions, as well as on methods commonly applied in immunology that require bioinformatic expertise. Moreover, we will present ongoing projects and highlight common challenges encountered by bioinformaticians and researchers in the field of immunology.

This course will not go into detail of the analysis of the different datasets, but rather provides an overview over the bioinformatics methods used in immunology.


This course is addressed to life scientists and bioinformaticians, from academia or industry, with little to no knowledge in immunology who are or will be working with immunological datasets.

Learning outcomes

At the end of the course, the participants are expected to:

  • list the different cell types of the immune system and their function.

  • appreciate the complexity of the immune system and overlaps with other systems.

  • plan an immunological experiment / judge the quality of the experimental setup.

  • explain how to analyze different types of data, what the data looks like, and what pitfalls can occur during analysis.


Knowledge / competencies

This course is designed for beginners in R. The competences and knowledge levels required correspond to those taught in courses such as: First Steps with R in Life Sciences or Introduction to statistics with R.

Evaluate your R skills with the following self-assessment.


You are required to bring your own laptop with a Wi-Fi connection, and the following software installed PRIOR to the course: R, R Studio. A list of packages will be provided in due time.

Schedule - CET time zone

9:15 - 10:30 Introduction into the immune system

10:30 - 10:45 Coffee Break

10:45 - 11:30 Systems immunology – embracing the complexity of the immune system

11:30 - 12:15 Flow cytometry in Biomedical Research

12:15 - 13:15 Lunch

13:15 - 14:45 Methods commonly used in immunology and how to analyze the data (e.g. RNA sequencing, spacial sequencing, RCR/BCR analysis)

14:45 - 15:00 Coffee Break

15:00 - 16:45 Hands on: Totalseq /Citeseq

16:45 - 17:30 Current research topics, methods, and problems


The registration fees for academics are 100 CHF and 500 CHF for for-profit companies.

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.

Deadline for free-of-charge cancellation is set to 11/10/2024. 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.

This course will start at 9:15 and end around 17:30.

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

Additional information

Coordination: Valeria Di Cola, SIB Training group.

We will recommend 0.25 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.