This course will focus on the analysis of data from genomic studies of cancer. It will also highlight the application of transcriptomic analysis and single-cell technologies in cancer. Talks and interactive sessions will give an insight into the bioinformatic concepts required to analyse such data, whilst practical sessions will enable the participants to apply statistical methods to the analysis of cancer genomics data under the guidance of the 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 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 08:45 – 17:00 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?

We welcome applications from PhD students, post-doc researchers, and those working in industry. This course is well-suited for those who are applying, or planning to apply, high throughput sequencing and single-cell technologies in cancer research and wish to familiarise themselves with bioinformatics tools and data analysis methodologies specific to cancer data.

Familiarity with the technology and biological use cases of high throughput sequencing (HTS) is required, as is some experience with R/Bioconductor (basic understanding of the R syntax and ability to manipulate R objects) and the Unix/Linux operating system. There are many tutorials available online and here are some that may be of help:

To complete the following suggested tutorials you may want to install Ubuntu for Windows Users if you are using a computer with a Windows Operating System.

• Learn Enough Command Line to Be Dangerous – tutorial
• Learn Enough Command Line to Be Dangerous – manipulating files
• Introduction to R tutorials – Programming basics (if you are completing the R tutorials make sure you complete this one first)
• Introduction to R tutorials –  Data Visualisation Basics

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:

• Evaluate the applications and challenges of HTS in the study of cancer genomics
• Detect, visualise, and annotate copy number variation
• Interpret complex genomic rearrangements such as structural variants
• Explain the principles of tumour purity, heterogeneity, and evolution and how we detect or quantify them using bioinformatic approaches
• Explore the application of CRISPR-Cas9 genome editing in cancer studies
• Perform alignment and quantification of expression of RNA-seq datasets
• Explore the application of single-cell sequencing in cancer studies

Course content

During this course you will learn about: 

• Application of high throughput sequencing (HTS) in cancer
• Introduction to cancer genomics and epigenetics
• Structural variation, SNV and CNV analysis, and data visualisation
• Application of CRISPR-Cas9 genome editing in studying cancer
• RNA-seq analysis (both short and long reads)
• Single-cell research in cancer

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 31 March 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 15 April 2024. If you have any questions regarding the application process please contact Meredith Willmott.

Course materials

The course materials from the 2023 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 2024 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.