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Study information

Bioinformatics, Interpretation and Data Quality Assurance in Genome Analysis ONLINE

Module titleBioinformatics, Interpretation and Data Quality Assurance in Genome Analysis ONLINE
Module codeHPDM041Z
Academic year2021/2
Credits15
Module staff

Dr Michael Weedon (Convenor)

Duration: Term123
Duration: Weeks

8

Number students taking module (anticipated)

30

Module description

The main challenge for application of genomic data is in its analysis and interpretation. The aim of this module is to enable you to gain the knowledge and understanding required to critically interpret existing genomic research, and develop the skills to formulate your own research questions as well as to collect, analyse and interpret genomic  data using a basic range of statistical and bioinformatics techniques.

Module aims - intentions of the module

The module will cover the fundamental principles of informatics and bioinformatics applied to clinical genomics. You will find and use major genomic and genetic data resources; software packages, in silico tools, databases and literature searches to align sequence data to the reference genome. You will also critically assess, annotate and interpret findings from genetic and genomic analyses. Theoretical sessions will be coupled with practical assignments performing analysis and annotation of predefined data sets. Upon completion of this module you will be eligible to base your MSc research project on data from the ‘100,000 Genomes Project’.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

  • 1. Apply basic computational skills and application of statistical methods for the handling and analysis of sequencing data for application in both diagnostic and research settings.
  • 2. Demonstrate practical experience of the bioinformatics pipeline through the ‘Genomics England’ programme.
  • 3. Analyse the principles applied to quality control of sequencing data and filtering strategies to identify pathogenic mutations in sequencing data.

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

  • 4. Justify and defend the place of Professional Best Practice Guidelines in the diagnostic setting for the reporting of genomic variation.
  • 5. Interrogate major data sources and integrate with clinical data, to assess the pathogenic and clinical significance of the genome result.

ILO: Personal and key skills

On successfully completing the module you will be able to...

  • 6. Critically reflect on personal practice and make connections between known and unknown areas, to allow for personal development, adaptation and change.
  • 7. Respond to innovation and new technologies and be able to evaluate these in the context of best practice and the need for improved service delivery.
  • 8. Communicate accurately and effectively with peers, tutors and the public.

Syllabus plan

Whilst the module's precise content may vary from year to year, an example of an overall structure is as follows:

 

  • 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.
  • How to determine the analytical sensitivity and specificity of genomic tests.
  • Use of tools to call sequence variants e.g. GATK, annotation of variant-call files using established databases.
  • Filtering strategies of variants, in context of clinical data, and using publically available control data sets
  • Use of multiple database sources, in silico tools and literature for pathogenicity evaluation, and familiarisation with the statistical programmes to support this.
  • Principles of integration of laboratory and clinical information, and place of best practice guidelines for indicating the clinical significance of results.
  • Principles of downstream functional analysis e.g. knock-outs, and other cellular model.
  • How to analyse genomic data to identify epigenetic and other variation that modifies phenotype.

Practice in examples of analysis of genomic data in the Training Embassy within the ‘Genomics England’ Data Centre.

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching ActivitiesGuided independent studyPlacement / study abroad
01500

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Guided independent study10Tutor guided online discussion forum
Guided independent study10Tutor guided online workshop
Guided independent study10Preparation of case based report
Guided independent study25Answering online problem solving questions (including preparation)
Guided independent study95Online resources and independent guided literature research.

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Online resources and independent guided literature research1-2 hours weekly1-8Written
Participation in online discussion forum1 hour weekly1-8Written

Summative assessment (% of credit)

CourseworkWritten examsPractical exams
10000

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Case-based report1002500 words1-5Written
0
0
0
0
0

Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Case-based report (100%) 2500 wordsCase-based Report1-5Typically within six weeks of the result

Re-assessment notes

Please refer to the TQA section on Referral/Deferral:

http://as.exeter.ac.uk/academic-policy-standards/tqa-manual/aph/consequenceoffailure/

Indicative learning resources - Basic reading

  • Read, A. and Donnai, D. (2015). New clinical genetics. Bloxham, Oxfordshire: Scion.
  • Turnpenny, P. and Ellard, S. (2012). Emery's elements of medical genetics. Philadelphia: Elsevier/Churchill Livingstone. (electronic access through University of Exeter library)
  • Strachan, T., Read, A. and Strachan, T. (2011). Human molecular genetics 4 . New York: Garland Science.
  • Strachan, T., Goodship, J. and Chinnery, P. (2015). Genetics and genomics in medicine. New York: Garland Science.

Indicative learning resources - Web based and electronic resources

http://vle.exeter.ac.uk/course/view.php?id=6145

Key words search

Alignment, data analysis, bioinformatics, sequencing, filtering

Credit value15
Module ECTS

7.5

Module pre-requisites

N/A

Module co-requisites

N/A

NQF level (module)

7

Available as distance learning?

No

Origin date

01/12/2015

Last revision date

12/05/2021