Aim of this module
Advances in genomics are leading to a better understanding of genetic variation and the role that such variation plays in human health and infectious disease. Such insights are important in predicting inherited disease risks, understanding and classifying cancer, predicting individuals’ responses to drug treatment, or better understanding the spread of drug-resistant pathogens. This module will develop the trainee’s fundamental understanding of genetic variation and its role in disease. It will also build on the trainee’s bioinformatics knowledge of the wide range of tools and resources that are used in bioinformatics to capture this knowledge, and how such tools are used by Clinical Scientists to support patient-centred care, diagnosis and treatment. A strong emphasis will be placed on ethical and confidentiality issues with such sensitive data.
This module will enable the trainee to apply their knowledge of genetic variation and its role in disease in the context of bioinformatics and the wide range of tools and resources that are used in clinical bioinformatics to capture data and support patient-centred care, diagnosis and treatment. A strong emphasis will be placed on ethical and confidentiality issues with such sensitive data. An awareness of the impact of interpretations given on clinical and public health action should be paramount when communicating the analysis of data to multi-disciplinary teams.
For some trainees this will involve applying their knowledge of pathogen variation in bacteria and viruses and how this relates to inference of transmission and resistance to apply bioinformatics tools and algorithms to support outbreak analysis and pathogen characterisation.
In the context of both human and microbes:
|Number||Work-based learning outcome||Title||Knowledge|
Annotate variation data in the context of a specific acquired or inherited disease or genetic investigation.
Use appropriate literature to summarise the role of clinical genetics in personalised healthcare in a written report or oral presentation.
Document the analysis process to annotate variation data in the context of a specific genetic investigation and use this to develop an enhanced testing strategy.
Explain how to choose and apply major bioinformatic resources for clinical diagnostics in this disease/service area and how their results are integrated with other lines of evidence to produce clinically valid reports.
Develop a strategy to modify or assemble tools, pipelines and processes for this disease/service area.
Develop an implementation plan for the recommended strategy in the service/disease area.
|You must complete|
|2 Case-based discussion(s)|
|2 of the following DOPS / OCEs|
|Use the ensemble variant effect predictor tool to annotate a VCF file See if any genes in a CMV are present in the OMIM morbid database||DOPS|
|Annotate a splice site mutation using more than one algorithm, and explain their relative strengths weaknesses.||DOPS|
|Interpret missense analysis results e.g. SIFT and PolyPhen||DOPS|
|For a disease select the appropriate LSDB i.e BRCA BIC etc. Select based on ease of integration and quality||DOPS|
|Present findings of the interpretation of a missense variant to a MDT meeting||OCE|
The academic parts of this module will be detailed and communicated to you by your university. Please contact them if you have questions regarding this module and its assessments. The module titles in your MSc may not be exactly identical to the work-based modules shown in the e-portfolio. Your modules will be aligned, however, to ensure that your academic and work-based learning are complimentary.
Clinical application of bioinformatics
Specific databases capturing SNP/disease associations
Specific clinical analysis software
Disease and phenotype ontologies
Reporting of results
Ethics, confidentiality and governance