This course covers the analysis of scRNA-seq data using R and command line tools. Participants will be guided through droplet-based scRNA-seq analysis pipelines from raw reads to cell clusters. They will explore and interpret data using R as well as the Single Cell Expression Atlas. Finally participants will put their knowledge into practice through a group challenge on the final two days.

Please note that participants will not analyse their own data as part of the course. There will, however, be ample opportunity to discuss their research and ideas with other course participants and trainers.

Who is this course for?

This course is aimed at wet-lab researchers who are generating, planning on generating, or working with single cell RNA sequencing data.

Prerequisites

Participants will require a basic knowledge of the Unix command line, the Ubuntu 18 operating system and the R statistical packages. We recommend these free tutorials:

• Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix
• Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training
• Basic R concept tutorials: www.r-tutor.com/r-introduction

What will I learn?

Learning outcomes

After this course, you should be able to: 

• Explain the steps in the scRNA-seq pipeline
• Repeat the course analysis of scRNA-seq data from extraction to cluster maps
• Recognise decision-making steps along the analysis pipeline and justify your decisions, from experimental design to final visualisation
• Employ appropriate data standards for repository submission and contribution to global cell atlases

Course content

During this course you will learn about:

• Single cell RNA-seq experimental design
• scRNA-seq analysis pipelines for droplet-based data
• EMBL-EBI Single Cell Expression Atlas Service
• Human Cell Atlas data & metadata standards

Trainers

Registration is now closed.