During the summer semester of 2024, the Single-Cell Center, in cooperation with the Collaborative Research Centers “DECIDE” and “CARDIO-IMMUNE INTERFACES,” offers a series of courses designed to introduce single-cell data analysis.
Data visualization – May 2, 5 pm
The workshop aims to enhance data communication by focusing on effective data visualization principles, emphasizing clarity and accuracy. Participants will learn to select appropriate plots for their data, avoiding common pitfalls. The course covers single-cell RNA-seq visualization using R and ggplot2, equipping participants with essential tools for impactful data presentation.
Single-cell RNA-seq analysis I – May 16, 5 pm
The course “Single-cell RNA-seq analysis I” provides a comprehensive introduction to single-cell data analysis with the popular R package Seurat. Participants will examine key concepts such as count matrices, Seurat objects, and explore the essential quality control and data processing steps. In this course, attendees will learn how to conduct their own data analysis on single-cell data, while also gaining insights into the technical backgrounds and associated potential pitfalls.
Single-cell RNA-seq analysis II – May 20, 5 pm
The course “Single-cell RNA-seq analysis II” will cover various topics on how to deal with real-world data, including hashtag demultiplexing, batch correction, robust differential gene expression analysis, and differential abundance testing. This course will provide attendees with strategies on how to handle typical experimental designs (e.g. hashtag multiplexing, multiple batches) and with first skills to gain biological insights from these data.
Spatial transcriptomics analysis – July 4, 5 pm
Participants will explore state-of-the-art, near single-cell resolution spatial transcriptomics data on the Curio Seeker platform. They will understand the data structure, challenges, and strategies for analysis. The attendees will discover biological insights by considering spatial context and cell-cell interactions going beyond traditional scRNA-seq methods.
The instructors are Florian Erhard, Alexander Leipold, and Anastasiya Grinko. The course is primarily tailored for members of the Collaborative Research Centers.
