Date: 7 - 9 April 2025 in Berlin
➚ Register
Audience: Stem cell biologists (PhD students, Postdocs, Research associates) working with single-cell genomics data.
Beginners (Group B): first steps into single-cell data, little to no coding experience
Advanced (Group A): have already had hands-on data and some coding experience, ideally in Python.
Goal: This workshop aims to equip stem cell biologists with a comprehensive introduction to computational single-cell genomics, focusing on data analysis using software from the scverse ecosystem. Designed for both beginners and advanced users, the workshop will provide hands-on experience with key tools for processing and analyzing multiple single-cell data modalities, including:
Single-cell RNA sequencing (scRNA-seq)
Spatial transcriptomics
Single-cell ATAC sequencing (scATAC-seq) (for advanced attendees only)
The workshop will provide preliminary materials including online consulting sessions to assist beginners set up their programming environment and resources to enable them to begin programming in Python. By the end of the workshop, participants will:
Understand the fundamental concepts of single-cell data analysis.
Learn best practices for preprocessing, quality control, clustering, visualization, and others using tools like scanpy, squidpy and muon.
Gain hands-on experience with advanced analysis techniques such as trajectory inference, batch-effect correction, multi-omics data integration, and spatial analysis. Develop skills to interpret single-cell data in the context of stem cell biology.
The last day will give participants the opportunity to apply their new skills on either their own data or curated mini-projects with the guidance of the trainers.The workshop (syllabus below) will be preceded by optional preliminary help sessions. The help sessions are intended to encourage participants who are new to programming and wish to get a head-start. Interested participants will be able to contact one of the presenters (through Zulip or Zoom) regarding any preliminary materials or issues with software installations.
Fee (just for the course, no hotel, no dinner, no travel reimbursement included):
regular non-member - 320 €
regular member - 260 €
student non-member - 260 €
student member - 210 €
Register ➚ here
Program (Syllabus):
Monday, 07 April 2025
| 09:00 - 10:00 |
AnnData in single-cell (scverse speaker) |
| 10:00 - 11:30 |
i Basic pre-processing of single-cell RNA-seq data
ii Batch effect correction
iii Interpretive analysis using pydeseq2 |
| 11:30 - 12:00 |
Coding practice and troubleshooting session |
| 12:00 - 13:00 |
Lunch |
| 13:00 - 14:30 |
Group B (Beginners): Trajectory analysis in single-cell RNA-seq
Group A (Advanced): scATAC-seq preprocessing with ArchR/SCENIC |
| 14:45 - 16:15 |
Continued:
Group B: Trajectory analysis in single-cell RNA-seq
Group A: scATAC-seq preprocessing with ArchR/SCENIC |
| 16:30 - 17:30 |
Coding practice and troubleshooting session |
Tuesday, 08 April 2025
| 09:00 - 10:00 |
Scientific lectures |
| 10:00 - 11:30 |
Advanced scRNA-seq analyses:
i Ligand-receptor interactions
ii Differential cellular abundance |
| 11:30 - 12:00 |
Coding practice and troubleshooting session |
| 12:00 - 13:00 |
Lunch |
| 13:00 - 14:30 |
Spatial data pre-processing and analysis |
| 14:45 - 16:15 |
Continued:
Spatial data pre-processing and analysis |
| 16:30 - 17:30 |
Coding practice and troubleshooting session |
Wednesday, 09 April 2025
| 09:00 - 10:00 |
Scientific lectures |
| 10:00 - 11:30* |
Option 1: Reproduce figures from a published paper
Option 2: Get consultative feedback on your own analysis |
| 11:30 - 12:00 |
Short presentation from interested participants |
| 12:00 - 13:00 |
Fare well |
* For the last day, the participants may choose to either reproduce figures from a published paper using the code/tools we discuss during the previous two days or get consultative feedback on their analysis on their own data. Please be mindful of the presenters’ time to ensure you have only consultative questions and not debugging or troubleshooting questions as that may not be feasible during the allocated time.