Wolfson Institute for Biomedical Research


Scanning electron micrograph of the dendrites of a cerebellar Purkinje cell - Hausser Lab


MEDC0086 Multiomics and ethics

MEDC0086 Multiomics and ethics

Module Title

 Multiomics and ethics
Module CodeMEDC0086
Module LeaderDr Paul Frankel
Short description

Precision medicine has three essential attributes:

1)            A mechanistic understanding of the aetiology and pathogenesis of disease. 

2)            The ability to detect (diagnose in the clinical laboratory) specific causal factors.

3)            The ability to specifically treat the underlying cause(s)

The module will focus on the second and third of these attributes.

The ‘omics technologies’ comprise genomics, proteomics and transcriptomics and the resulting deluge of big data necessitates that researchers understand the basic science behind these technologies and the way in which they are applied to the study and practise of human disease.

Module aims

  • How the basic science works to generate the omics data.
  • Large datasets and the ways in which they can be assessed and handled/
  • The integration of this data to establish diagnoses that can lead to precision treatment.
  • The emphasis will be on teaching principles and on critical analysis of data rather than to try to communicate the whole breadth of the field/
  • Regulatory aspects are important to the use of omics data: is the privacy of patients respected and ensured by the techniques used for anonymization, what are the risks associated with data leaks?
  • Principles and techniques
  • Diagnostics, omics and phenotyping.
  • Regulatory landscape and brief legal framework

Learning Outcome

  • Have acquired a knowledge base of modern large scale dataset techniques frequently referred to as 'omics' data.
  • Understand how such datasets relate to human disease.
  • Be able to critically analyse omics data.
  • Understand ethical issues such as patient privacy, the risks of omics data being disclosed, and how this relates to the regulatory landscape.
Module assessment 50% course work + 50% unseen 1 hour exam