Advanced Topics in Single-Cell Transcriptomics

26-29 April 2022

Grégoire Rossier

Dr. Grégoire Rossier, SIB, Lausanne

Dr. Charlotte Soneson (FMI/UniBas) Dr. Panagiotis Papasaikas (FMI/UniBas) Prof. Michael Stadler (FMI/UniBas) Prof. Mark Robinson (UniZH)
Ms Emma Dann, University of Cambridge, UK
Mr. Giovanni Palla, Helmholtz Zentrum München, DE

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 transcriptomics 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 Deep Generative Networks and their use in single cell analysis

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.

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 with iSEE
• Spatial transcriptomics

Friday 29 April

• Deep Generative Networks
• Automated cell type annotation

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

UNIBAS

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 [email protected].

This course is co-organized by the doctoral program StarOmics and SIB. A certain number of places will be attributed in priority to StarOmics members (so mention it if you are part of our program).

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.

For technical reasons, there will be the information that the registration fees are 240 CHF, but it will be free for StarOmics students.

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.

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For more information, please contact [email protected] or StarOmics