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The University of Southampton

MEDI6237 Genomic Technologies and Basic Informatics

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, together with current technologies routinely used to investigate genomic variation in both clinical and research settings. The module will cover the fundamental principles of informatics and bioinformatics applied to genomics. The students will be taught to find and use major genomic and genetic data resources; use software packages, in silico tools, databases and literature searches. Specifically, students will learn to align sequence data to the reference genome, critically assess, annotate and interpret findings from genetic and genomic analyses. Theoretical sessions will be coupled with practical assignments of analysing and annotating predefined data sets. A comprehensive introduction to the functional interpretation of genomic data will be included. Students will also learn about the strategies employed to evaluate pathogenicity of variants for reporting. This is a core module that is central to the MSc programme in Genomics as it will provide the student with the skills to analyse genomic data in a graphical user interface (GUI).

Aims and Objectives

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Critically evaluate a range of up-to-date sequencing technologies and select appropriate techniques for genomic testing
  • Acquire relevant basic computational skills and understanding of statistical methods for handling and analysing sequencing data for application in both the diagnostic and research settings
  • Develop basic workflows for automated analysis of next generation sequencing (NGS) data using a graphical user interface
  • Critically appraise up-to-date tools for quality control of data, sequence alignment, variant calling, annotation and variant filtration to identify potentially pathogenic variants
  • Interrogate major data resources of genomic sequence variation and biological pathways, (e.g. EVS, dbSNP, ClinVar, etc.), to assess the pathogenic and potential clinical significance of genome results


• Basis of genotyping and detection of genetic variation: Application of whole exome and whole genome and targeted sequencing technologies across a variety of platforms • Genomic testing strategies as: gene focused, multiple genes, or whole genome or exome, and for detection of sequence, copy number or rearrangements • Aligning genome data to reference sequence using up to date alignment programmes (e.g. BWA) • Assessment of data quality through application of quality control measures • Use of tools to call sequence variants e.g. GATK, annotation of variant-call files using established databases • How to determine the analytical sensitivity and specificity of variant detection • Filtering strategies of variants, in context of clinical data, and using publicly-available control data sets • Use of multiple database sources, in silico tools and literature for pathogenicity evaluation, and familiarity with the statistical programmes to support this • Principles of downstream functional analysis e.g. knock-outs, knock-ins, CRISPR and other cellular models

Learning and Teaching

Teaching and learning methods

The module will comprise two blocks of 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 Study165
Total study time200


Assessment Strategy

The assessment for the module provides you with the opportunity to demonstrate achievement of the learning outcomes. In addition to the summative assessments, during the course of the module there will be opportunities to obtain feedback in the form of unassessed, formative activities.


Workshop activities


MethodPercentage contribution
Data analysis project  (3500 words) 100%


MethodPercentage contribution
Data analysis project  (3500 words) 100%

Repeat Information

Repeat type: Internal & External

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