Single-Cell RNA-Seq Workshop 2024

The Single-Cell RNA-Seq Workshop is designed to provide a thorough introduction to the analysis of single-cell RNA sequencing data. Through a combination of lectures and hands-on exercises, participants will learn how to process, analyze and integrate single-cell data using industry-standard tools and techniques. Topics covered include sequencing technologies, data quality control, preprocessing, dimensional reduction, clustering, trajectory inference, differential expression analysis, and multi-sample integration.

By the end of the workshop, attendees will have the skills and confidence to perform custom analyses and gain new insights into complex biological systems. This workshop is ideal for researchers and students with little or no prior experience in single-cell RNA-seq analysis, as well as those seeking to update their skills and knowledge.

This workshop has been adapted to the needs of beginners in the field of (biological) data analysis and comprises these three course modules:

Applications of NGS in Single-Cell analysis:
During the first part of the workshop, participants learn about sequencing technologies, bioinformatics file formats, and sample library processing. They also become familiar with the Cell Ranger platform and how to navigate the Linux command line and file system.
Single-sample analysis with R-Seurat:
The second part of the workshop focuses on single-sample analysis using R-Seurat. Participants learn standard preprocessing steps, dimensional reduction techniques, clustering, and marker detection, while creating extensive diagnostic graphics with R.
Data integration and multi-sample analysis:
The final part of the workshop covers data integration and multi-sample analysis, including the integration of different sources of data, handling of batch effects and soft integration, and differential expression analysis between cell clusters and conditions. Participants also learn about multi-modal analysis and apply their new skills to challenging exercises.

Detailed Course Program

Applications of NGS in Single-Cell analysis

Introduction to sequencing technologies from a single-cell perspective
Understanding plate-based and droplet-based methodologies
Introduction to the Linux command line and navigating the file system
Overview of bioinformatics file formats (e.g. FASTQ, FASTA, GTF)
Processing sample libraries: Alignment, filtering, and expression count matrices
Using the Cell Ranger platform to process and QC Chromium 10X data

Single-sample analysis with R-Seurat

Familiarise with data processing in R
Standard preprocessing steps: filtering cells, data normalisation, feature selection
Dimensional reduction: principle component analysis, determining the dimensionality
Non-linear dimensional reduction with tSNE and UMAP
Clustering in Seurat by k-nearest neighbours
Marker detection for cluster annotation
Creating extensive diagnostic graphics with R
Single-cell trajectory inference and RNA velocity

Data integration and multi-sample analysis

Data integration: combining different sources of data
Cell-label transfer
Handling batch effects and soft integration
Differential expression between cell clusters and conditions
Multi-modal analysis: incorporating high dimensional -omics data
Applying your new skills by working on challenging exercises

Speakers

Dr. Helene Kretzmer (Max Planck Institut for Molecular Genetics)
Helenes expertise is in the integration of multiple forms of next- and third-generation sequencing data, including large single-cell, epigenomic and long-read Nanopore data, to better understand how genome regulation changes to support various developmental processes or malignant transformation. Publications

Dr. Adam Nunn (ecSeq Bioinformatics GmbH)
Adam is an expert bioinformatician skilled in developing data analysis pipelines. He specializes in whole genome DNA-Seq, de-novo genome assemblies, bulk RNA-Seq, and single-cell RNA-Seq. At ecSeq Bioinformatics, he is the go-to specialist for single-cell RNA-Seq analysis. Adam's expertise enables him to extract valuable insights from complex datasets, unraveling gene expression patterns at the single-cell level. Publications

Requirements

The target audience are biologists or data analysts with no or little experience in developing computational pipelines for data analysis. A superficial understanding of molecular biology (DNA, RNA, gene expression, PCR, ...) is assumed, as examples will be given in the context of this field.

Some familiarity with a command line interface (e.g. Linux, Mac OS X) and a minimal understanding of object-oriented programming (with e.g. Python or Java) is recommended but not required.

Printed course materials
Catering during the workshop
Conference dinner
High-performance computer (no laptop needed)
Downloadable environment for seamless continuation / repetition after the course
Certificate

Attendance

Location: PC-College, Stresemannstraße 78, 10963 Berlin, Germany
Language: English
Available Seats: 30 (first-come, first-served)

Registration Fee: 1089 EUR (excluding VAT)

Travel Information - Berlin

Key dates

Opening Date of Registration: Dec 18, 2024
Closing Date of Registration: April 26, 2024
Workshop: May 6-8, 2024 from 9 am to 5 pm

"Overall, I was extremely satisfied with this workshop. As a beginner to any sort of RNA analysis this was a great introduction and along with the course material book, I believe I could now tackle a dataset independently which is exactly what I wanted from this course. So, thank you all very much for organising such a superb workshop!" Charlotte Dunne, Pantherna Therapeutics, Germany

"I am writing to express my utmost satisfaction with the Bioanalysis in Single Cell Sequencing course. The comprehensive content covered every aspect needed, offering a full understanding of the topic. I would like to extend my gratitude to the exceptional instructors whose friendliness and eagerness to answer all our queries made the learning experience truly enriching. Their knowledge and commitment to our understanding were apparent and highly appreciated. I am looking forward to applying the skills and knowledge I have gained in my future work." Wilson DSB, Sanofi, Paris, France

"It was an extremely condensed, organised and highly intellectual program. After the course, I felt comfortable with the material and the analysis of single cell RNA sequencing. I enjoyed every bit of the course, including the social aspect. I also appreciated that the tutors took their time to explain every question even when we were running short of time." Eugene Padi, Rigshospitalet, Denmark

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When you register for this workshop you are agreeing with our Workshop Terms and Conditions. Please read them before you register.

Any Questions? Please feel free to contact our events team.

ecSeq Bioinformatics GmbH
Sternwartenstr. 29
D-04103 Leipzig
Germany
Email: events@ecSeq.com

Single-Cell RNA-Seq Data Analysis: A Practical Introduction
From Data Processing to Multi-Sample Integration

In a nutshell

Scope and Topics

Our Philosophy

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