This course covers the analysis of single cell RNA-seq data using Python and command line tools. Participants will be guided through droplet-based single cell RNA-seq analysis pipelines from raw reads to cell clusters. Furthermore, you'll learn how to generate common plots for visualisation and analysis of gene expression data, including TSNE, UMAP, and violin plots.

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.

Virtual course

Participants will learn via a mix of pre-recorded lectures, live presentations, and trainer Q&A sessions. Practical experience will be developed through trainer-led computational exercises and group activities. Live sessions will be delivered using Zoom with additional support and asynchronous communication via Slack.

Pre-recorded material may be provided before the course starts that participants will need to watch, read or work through to gain the most out of the actual training event. In the week before the course, there will be a brief induction session. Computational practicals will run on EMBL-EBI's virtual training infrastructure, meaning participants will not require access to a powerful computer or install complex software on their own machines.

Participants will need to be available between the hours of 09:00 – 17:30 BST each day of the course. Trainers will be available to assist, answer questions, and provide further explanations during these times.

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 are required to have basic experience with the Unix/Linux command line. Basic knowledge of Python is essential.  We recommend you go through these free tutorials before attending the course:

• Basic introduction to the Unix environment: https://swcarpentry.github.io/shell-novice/index.html 
   
• Introduction to programming in Python: http://swcarpentry.github.io/python-novice-gapminder/ 

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 technologies
• Single cell RNA-seq experimental design
• scRNA-seq analysis pipelines for droplet-based data:
  • Align reads to a genome reference and count the number of read per gene
  • Reading the count data
  • Quality control
  • Normalisation
  • Data set integration
  • Clustering 
  • Differential expression
  • Abundance analyses 
  • Spatial transcriotomics
• EMBL-EBI Single Cell Expression Atlas Service
• Single cell data submission

Trainers

Please read our support page before starting your application. In order to be considered for a place on this course, you must do the following:

• Complete the online application form.
• Ensure you add relevant information to the ‘submission details’ section where you are asked to provide information on your:
  • pre-requisite skills and knowledge
  • current work and course expectations
  • data availability
• Upload one letter of support from your supervisor or a senior colleague detailing reasons why you should be selected for the course.

Please submit all documents during the application process by 23:59 on 09 June 2024. Items marked * in the application are mandatory. Incomplete registrations will not be processed. 

All applicants will be informed of the status of their application (successful, waiting list, unsuccessful) by 26 June 2024. If you have any questions regarding the application process please contact Juanita Riveros. 

Fee bursaries

Limited financial assistance is available in the form of a registration fee waiver, which will cover the registration fee to be paid to attend the course. The recipient will be informed about their bursary application together with the outcome of their course application.
You may apply for financial assistance when submitting your application. During the application, you will be asked to justify your need to receive a fee bursary and how your attendance will make a difference to your career. Application for financial support will not affect the outcome of your application.
The scientific organisers will select the recipient of all financial assistance during the participant selection process. Bursary selection results do not impact your admission to the course. Selection is based on scientific merit, your current work or study location, the reasons for needing financial support, and the impact this event will have on your career.

Posters

All participants are expected to present a poster virtually. Successful applicants will be provided with further information and asked to submit this upon registration. 

We expect the posters to act as a talking point between you, other participants and the trainers on the course. They should give the reader an idea of the work you are engaged in, what you are planning to do next, and anything of interest that might be useful for sharing with the gathered participants.