Gain an introduction to the technology, data analysis, tools, and resources used in RNA sequencing and transcriptomics. The content will provide a broad overview of the subject area, and introduce participants to basic analysis of transcriptomics data using the command line. It will also highlight key public data repositories and methodologies that can be used to start the biological interpretation of expression data. Topics will be delivered using a mixture of lectures, practical exercises, and open discussions. Computational work during the course will use small, example data-sets; and there will be no opportunity to analyse personal data.

Please note that this course covers different topics related to bulk RNA-Seq data analysis. Other related techniques such as single-cell and spatial transcriptomics will not be covered. Nonetheless, the overview lecture will describe the potentials and limitations of the most commonly used RNA-Sequencing analysis techniques and the context in which they are used. If you are seeking training on single-cell please consider applying to the 2025 ‘Single-cell RNA-seq analysis with Python’ virtual course, which will run about the same dates.
 

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 group activities and trainer-led computational exercises. 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 08:00 – 18:00 GMT 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 life science researchers, wet and/or dry lab,  wanting to learn more about processing RNA-seq data and later downstream analysis. It will help those wanting a basic introduction to handling RNA-seq data, guiding them through several common approaches that can be applied to their own datasets. It features taught and practical sessions that cover how to interpret gene expression data and learn more about the biological significance of certain results.

Some experience with R and the linux-based command line is beneficial, but not essential. During the course some of the practicals will make use of a Linux-based command line interface, and R statistical packages. We recommend completing some basic tutorials on this topic in preparation for the upcoming course. There are many tutorials available online and here are some that may be of help:

• Introduction to the Unix environment – https://swcarpentry.github.io/shell-novice/index.html
• Introduction to R – https://swcarpentry.github.io/r-novice-inflammation/ 

Regardless of your current knowledge, we encourage successful participants to use these, and other materials, to prepare for attending the course and future work in this area.

What will I learn?

Learning outcomes

• Describe a variety of applications and workflow approaches for NGS technologies
• Apply bioinformatics software and tools to undertake analysis of RNA-seq data
• Evaluate the advantages and limitations of NGS analyses
• Interpret and annotate data with functional information using public resources

Course content

• High throughput sequencing technologies for RNA-Seq 
• Basics of experimental design
• RNA-seq file formats
• RNA-seq bioinformatics workflow steps following sequence generation
• Methods for transcriptomics; QC, mapping, and visualisation tools
• Data resources to assist in the functional analysis and interpretation of transcriptomic data
• Introduction to de novo approaches (options in the absence of a reference)
• Fundamentals of pipeline implementation (with Nextflow) for bulk RNA-seq analysis
• Data resources covered:
  • Expression Atlas
  • g:Profiler
  • Sequencing repositories: ENA, GEO, SRA

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 24 November 2024. Items marked * in the application are mandatory. Incomplete applications will not be processed. 

All applicants will be informed of the status of their application (successful, waiting list, unsuccessful) by 09 December 2024. If you have any questions regarding the application process please contact Barbara Etzi.

Registration fees

The registration fee includes: 

• access to the full five-day course programme
• access to a bespoke online course handbook
• secure community space on Slack
• virtual machine to work on that is accessed via the internet
• dedicated online support team
• course certificate on completion of the course

Financial assistance

Financial assistance is available for a limited number of participants on this course.

Registration fee waivers

We are able to offer a limited number of registration fee waivers for this course. If you receive a waiver, your registration fee will be reimbursed after you have completed the course.

You will need to apply for the fee waiver at the same time as submitting your application for the course, explaining why you require the waiver and how attending this course will benefit your career.

You will be informed about whether you have received the waiver at the same time as you hear about the application outcome for the course. If your course application is successful, you will need to pay the registration fee at the time you register. You will receive the waiver within a month of submitting your form. 

Terms and conditions

The scientific organisers will select the recipients of financial assistance during the course application selection process. Selection for financial support is based on scientific merit, your current work study or location, the reasons for needing financial support and the impact this event will have on your career. Priority will be given to applications from low and middle income countries.

Application for financial support will not affect the outcome of your course application.

Course materials

The course materials from the 2024 edition of the course are now live and available for you to use. They provide a mixture of pre-recorded lectures, presentations, and practicals from the course, and will give you a snapshot of what to expect in the 2025 edition.

Flash talks

All participants will be asked to give a short presentation about their research work as part of the course. These provide an opportunity to share their research with the other participants and provide a forum for discussion. Successful applicants will be required to submit their talks upon registration.