Virtual course

Cancer genomics

This course will focus on the analysis of data from genomic studies of cancer.  Lectures 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 lecturers.

Virtual course

The course will involve participants learning via pre-recorded lectures, live presentations, and trainer Q&A sessions. The content will be delivered over Zoom, with additional text communication over Slack.

Computational practicals will be run on EMBL-EBI's virtual training infrastructure; this means there is no need to have a powerful computer to run exercises or a requirement to install complex software before the course. Trainers will be available to provide support, answer questions, and further explain the analysis during these practicals.

Participants will need to be available between the hours of 09:30-18:00 BST each day of the course.

Who is this course for?

This course is aimed at advanced PhD students and post-doctoral researchers who are applying or planning to apply high throughput sequencing 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 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.

What will I learn?

Learning outcomes

After this 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
  • Indicate the principles of tumour purity, heterogeneity and evolution and how these influence/impact upon bioinformatics analysis
  • Perform alignment and quantification of expression of RNA-seq datasets

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


Ajay Mishra
Moritz Gerstung
Robert Eveleigh
McGill University, Canada
Tobias Rausch
EMBL, Heidelberg, Germany
Alexey Larionov
Medical Genetics Department, University of Cambridge, UK
Francesco Iorio
Wellcome Sanger Institute, UK
Mathieu Bourgey
McGill University and Genome Quebec Innovation Centre, Canada
Aurélie Ernst
DKFZ, Heidelberg, Germany
Ana Cvejic
Department of Haematology, University of Cambridge, UK
This course has ended

17 - 21 May 2021
Jane Reynolds

  • Ajay Mishra
  • Moritz Gerstung

Share this event with: