This course is co-organized by the doctoral program Staromics of the CUSO and SIB. A certain number of places will be attributed in priority to Staromics members.

Overview

In recent years, single-cell transcriptomics has become a widely used technology to study heterogeneous and dynamic biological systems. A large number of new tools and approaches have been developed for analyzing this new type of data. This course aims at discussing a selection of more advanced topics in single-cell omics data analysis, such as methods that are still being actively developed and go beyond the classical and well established analysis workflows. The typical steps in single-cell transcriptomics analysis will not be covered in this course and familiarity with them is considered a prerequisite.

Audience

This course is intended for computational biologists who are already familiar with single-cell transcriptomics analysis, who wish to learn about ongoing and future developments in the field.

Learning objectives

At the end of the course attendees will:

• be able to seamlessly integrate R and python in a single workflow;

• know how to perform RNA velocity analysis and how to generate input counts;
• become familiar with a widely used spatial transcriptomics technique;

• become familiar with the wide array of methods for differential discovery;
• become familiar with Deep Generative Networks and their use in single cell analysis;
• become familiar with tools for joint analysis of multi-omics single-cell data.

Prerequisites

Knowledge / competencies

• Extensive hands-on experience with analysis of scRNA-seq data, corresponding to an introductory Single-cell analysis course
• Ability to use packages and modules and write analysis scripts in R and Python
• Familiarity with software containers and git version control systems is a plus

Technical

Attendees should bring their own laptop. An online R / RStudio and python environment will be provided.

Tentative Program

Tuesday 26 April

• Combining R and python in a single analysis workflow
• Differential analysis
• RNA velocity

Wednesday 27 April

• Generating single cell data
• Multi-omics

Thursday 28 April

• Interactive visualization
• Spatial transcriptomics

Friday 29 April

• Deep Generative Networks
• Automated cell type annotation

Application

In order to provide active support and interactions, the number of participants to this course is limited. If there are more applications than available slots, participants from different groups with a demonstrated background required for this course and prior experience in single-cell analysis will be prioritized.

The registration fees for academics are 240 CHF. Participants from non-academic institutions should contact us before application.

Deadline for registration and free-of-charge cancellation is set to 01/04/2022. Cancellation after this date will not be reimbursed. Please note that participation to SIB courses is subject to our general conditions.

You will be informed by email of your registration confirmation.

Venue and Time

This course will be take place at the University of Basel from 9:00 to circa 17:00-17:30 .

Additional information

Coordination: Grégoire Rossier (SIB), Corinne Dentan (Staromics).

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.

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.