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This module will help you understand the theory and practice of omics at the genomic, transcriptomic, metabolomic and proteomic level. You will gain in depth knowledge of identifying the molecular and clinical features of cancer patient datasets and the steps involved in cancer evolution.

The first part of the module will introduce you to various multi-omics studies, including mutational signatures, transcriptomics, epigenomics, metabolomics and proteomics. You will get hands on experience exploring various profiling strategies including but not limited to; single cell and bulk sequencing and spatial transcriptomics.

The second part of the module teaches you about the concept of cancer evolution, which is a rapidly evolving field, and will cover the molecular and cellular mechanisms that allow cancer cells adapt to their environment, ultimately leading to tumour heterogeneity, immune system escape and treatment resistance.

This module will consist of a mixture of lectures, interactive small group tutorials, computer workshops and self-directed learning. You will be learning from experts in the field and will have ample opportunities to interact with PhD students, postdoctoral researchers and principal investigators. Topics covered in this module include:

· How to search for and analyse large-scale public datasets from cancer patients.

· Data types for; epigenomics, transcriptomics, functional genomics.

· Advanced sequencing technologies including; single cell, bulk, spatial transcriptomics.

· Basics of tumour evolution.

· Basic UNIX computational/programming skills.