Learn a complete, beginner-friendly single-cell workflow – from raw data processing and QC to cluster annotation, differential expression, and integration across samples.

Date: March 23-25, 2026
Location: Berlin, Germany
Link: Website

In a nutshell

• Understand sequencing technologies for single-cell analysis (plate-based vs droplet-based)
• Process, QC and analyze scRNA-seq data with a structured, reproducible workflow
• Identify, visualize and annotate cell clusters using practical marker-based strategies
• Integrate multi-sample data and handle batch effects with confidence

This workshop provides a thorough, hands-on introduction to single-cell RNA sequencing (scRNA-seq) data analysis. You will learn how to process, analyze, and integrate single-cell datasets using widely adopted tools and best practices.

We cover sequencing technologies, quality control and preprocessing, dimensionality reduction, clustering, trajectory inference, differential expression analysis, and multi-sample integration.

By the end of the workshop, you will be able to:

• Process 10x Chromium data with Cell Ranger and interpret key QC metrics
• Perform single-sample analysis in Seurat (filtering, normalization, PCA/UMAP, clustering, markers)
• Create diagnostic plots and make informed analysis decisions (not “click-and-hope”)
• Integrate datasets across samples/conditions, handle batch effects, and compare clusters via differential expression

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