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The University of Southampton

MEDI6131 Omics techniques and their application to Genomic Medicine

Module Overview

This module explores the state of the art genomics techniques used for DNA sequencing (e.g. targeted approaches, whole exome and whole genome sequencing) and RNA sequencing using highly parallel techniques, together with current technologies routinely used to investigate genomic variation in the clinical setting. This module will introduce the bioinformatics approaches required for the analysis of genomic data, which together with data governance covered in Module 1 will provide a solid foundation for the Bioinformatics module. The module will also cover the use of array based methodologies and RNA sequencing in estimating levels of protein expression, micro RNAs and long non–coding RNAs. A comprehensive introduction to metabolomics and proteomics, which are important for the functional interpretation of genomic data and discovery of disease biomarkers will also be included. Students will also learn about the strategies employed to evaluate pathogenicity of variants for clinical reporting.

Aims and Objectives

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Describe and critically evaluate a range of up-to-date genomic technologies and platforms used to sequence targeted parts of the genome or whole genomes
  • Discuss the application of other techniques (for example array comparative genome hybridisation, MLPA, qPCR) commonly used to interrogate genomic variation in the clinical setting using examples in cancer, rare inherited diseases and infectious diseases
  • Acquire the knowledge of selecting appropriate technology platforms for applications in medical genomics either for research or medical diagnostic purposes
  • Critique how these techniques and their applications in RNA expression can be applied to metabolomics and proteomic analysis
  • Discuss and critically appraise approaches to the bioinformatics analysis and interpretation of ‘omics’ data
  • Critically evaluate the different ‘omics’ technologies and platforms and their application to genomic medicine and the impact of personalised medicine
  • Discuss the approaches required to evaluate the pathogenicity of variants identified in whole genome sequencing and other genomic technologies.


Basis of genotyping and detection of genetic variation: Whole exome and whole genome sequencing, including library preparation methods, sequencing chemistries and platforms Brief overview of methodologies for detecting base substitutions (SNV), small insertions and deletions (indels), copy number variants (CNV) or rearrangements, to include Sanger sequencing, pyrosequencing, ARMS, MLPA, qFPCR, microarray Genomic testing strategies as: gene focused, multiple genes, or whole genome or exome, and for detection of sequence, copy number or rearrangements Additional techniques: RNA expression profiling (expression array) and RNA sequencing, metabolomics; proteomics techniques Overview of bioinformatics approaches to the analysis of genomic data Approaches to the evaluation of pathogenicity of variants in the context of an NHS clinical report.

Learning and Teaching

Teaching and learning methods

The module will comprise two blocks of two days' intensive on-site teaching, each followed by a period of independent study. A variety of learning and teaching methods will be adopted to promote a wide range of skills and meet the differing learning styles of the group. The on-site teaching will include seminars, practical demonstrations, discussions and exercises surrounding interpretation of data and clinical scenarios, and specialist lectures given by a range of academic and health care professionals. This will ensure a breadth and depth of perspective, giving a good balance between background theories and principles and practical experience. Off-site independent learning will take place on the virtual learning environment hosted by the UoS.

Independent Study122
Total study time150

Resources & Reading list

Genetics & Genomics in Medicine: Strachan, Goodship and Chinnery. 

Illumina resource base.

Ensembl work books.


Assessment Strategy

The assessment for the module provides you with the opportunity to demonstrate achievement of the learning outcomes. There will be two components to the assessment i) MCQ Examination, and ii) Annotated Scenario-based exercise. The pass mark for the module and all assessed components is 50%. If you do not achieve the pass mark on this module by achieving 50% or more in all components, you may still pass by compensation. To do this, you must achieve a qualifying mark of 40% in each of the assessed components. Each of the component marks is then combined, using the appropriate weighting, to give an overall mark for the module. If this overall mark is greater than or equal to 50% you will have passed the module. If your overall mark is less than 50% when the weighting has been applied to the components, you will have failed the module. If you have not achieved 40% or more on all components, you cannot use compensation and have failed the module. If you have failed the module, you will have the opportunity to submit work at the next referral (re-sit) opportunity using the method outlined below. You must achieve the pass mark in all referred components. On passing your referrals, your final module mark will be capped at 50%.


MethodPercentage contribution
Examination  (2 hours) 50%
Exercise  (1500 words) 50%


MethodPercentage contribution
Examination  (2 hours) 100%

Repeat Information

Repeat type: Internal & External

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