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. 

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.

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:

We recommend these free tutorials:

• 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

After the course you should be able to:

• 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

During this course you will learn about: 

• 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 long read analysis
• Fundamentals of pipeline implementation (with Nextflow) for bulk RNA-seq analysis
• Data resources covered:
  • Expression Atlas
  • g:Profiler
• Sequencing repositories: ENA, GEO, SRA

Trainers

This course opens applications on 28 July 2025. Click to register your interest using the button on the right-hand side of this course website to hear as the course develops. 

Once the course opens 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 GMT on 9 November 2025. 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 24 November 2025. If you have any questions regarding the application process please contact Anca Belu.

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.

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
• certificate on completion of the course

Financial assistance

Financial assistance is available to a limited number of participants attending this course.

Registration fee waivers

A limited number of registration fee waivers are offered for this course.

• Application process:
  • Apply for the fee waiver alongside your course application.
  • Provide a brief explanation of why you require the waiver and how attending the course will benefit your career.
• Notification:
  • You will be informed of your waiver status at the same time as the outcome of your course application.
  • If awarded, the registration fee will be waived entirely.

Terms and conditions

• Selection process: Recipients of financial assistance will be selected by the scientific organisers during the course application review.
• Selection criteria:
  • Selection is based on scientific merit, your current work or study location, the need for financial support, and the career impact of attending the course.
  • Priority will be given to applicants from Low- and Middle-Income Countries (LMICs).
• Fair consideration: Applying for financial assistance will not impact the outcome of your course application.

Course materials

The materials for the 2025 course are available for you to browse. These provide a snapshot of the content that will be covered in the 2026 course.