The aim of this module is to explore areas of ‘omics’ techniques and technologies, including their interpretation and application in key areas of genomic medicine, such as cancer, common and rare inherited diseases and infectious diseases, as well as research. Learning from this module will support those students undertaking a research project that may utilise large genomic data sets.
This module explores current genomics techniques used for DNA sequencing (e.g. targeted approaches, whole exome and whole genome sequencing) and RNA sequencing, using highly parallel methodologies, 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. 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. An 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.
- Basis of genotyping and detection of genetic variation.
- Whole exome and whole genome sequencing, including library preparation methods, sequencing chemistries and platforms.
- Overview of current methodologies for detecting single nucleotide variations (SNVs), small insertions and deletions (indels), copy number variants (CNVs) or rearrangements, to include Sanger sequencing, qFPCR, MLPA, aCGH, FISH.
- Genomic testing strategies as gene focused, multiple genes, or whole genome or exome, and for detection of sequence, copy number or rearrangements.
- Current methodologies to assess the transcriptome to include RNA expression profiling (expression array) and RNA sequencing.
- Overview of the metabolome and proteome, and how these change because of disease pathology.
- Overview of the methodologies that can be used to assess the metabolome and proteome.
- How information from the transcriptome, metabolome and proteome can be applied to the interpretation of genomic information.
- 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.
- How functional studies can be applied to the interpretation of pathogenicity.
15 Masters level credits
Module attendance required
Teaching delivered over 5 days.
Dr Samantha Butler (Principal Clinical Scientist, Familial Cancer and Molecular Pathology, West Midlands)
Dr Pauline Rehal (Principal Clinical Scientist, Molecular Pathology, West Midlands Regional Genetics Laboratory)
This module can be taken as a stand-alone assessed or non-assessed course.
You should have a good honours degree in a life sciences subject, although we will consider applicants with alternative qualifications and professional experience within the health service or other relevant background. You should either take our Fundamentals in Human Genetics and Genomics module first, or be able to show you have equivalent knowledge and understanding to enable you to benefit from this module.
Please contact the Programme Coordinator for further information at email@example.com