Module Catalogue 2026/27

Pre Requisite Comment

N/A

Co Requisite Comment

N/A

Aims

Students will gain an understanding of the probabilistic models in population genetics. They will be able to construct appropriate models for a range of scenarios including natural selection and geographical population structure and apply them to conduct and interpret common statistical tests. They will also gain an understanding of recombination and genome- wide data analysis, including common confounders of genome-wide association studies.

Outline Of Syllabus

Hardy–Weinberg laws and their implications for population frequencies of alleles, genotypes, and phenotypes. Assessment of Hardy–Weinberg model fit to data. Discrete-time Wright–Fisher models and their infinite-population coalescent limit. Properties of the standard coalescent, models of mutation, summary statistics and tests for coalescent model-fit and neutrality, e.g. Tajima's D. Recombination, linkage disequilibrium, association testing, an overview of genome-wide association studies.

Intended Knowledge Outcomes

At the end of the module it is expected that a student will be able to:
- Describe simple discrete-time reproductive models and use them to derive the Hardy–Weinberg equilibrium and standard coalescent models.
- Apply the predictions of coalescent theory to test for departures from neutrality.
- Evaluate the evidence for associations between genetic loci and Mendelian diseases.

Intended Skill Outcomes

At the end of the module it is expected that a student will be able to:
- Identify appropriate models for a wide variety of inference tasks in statistical genetics.
- Carry out appropriate data analysis in R, report on their analyses, and transfer these analytical skills to other contexts.

Students will develop skills across the cognitive domain (Bloom’s taxonomy, 2001 revised edition): remember, understand, apply, analyse, evaluate and create.

Teaching Rationale And Relationship

Lectures are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on marked work. Problem classes are used to help develop the students’ abilities at applying the theory to solving problems.

The teaching methods are appropriate to allow students to develop a wide range of skills. From understanding basic concepts and facts to higher-order thinking.

Assessment Rationale And Relationship

A substantial formal unseen examination is appropriate for the assessment of the material in this module. The format of the examination will enable students to reliably demonstrate their own knowledge, understanding and application of learning outcomes.

Examination problems may require a synthesis of concepts and strategies from different sections, while they may have more than one way for solution. The examination time allows the students to test different strategies, work out examples and gather evidence for deciding on an effective strategy, while carefully articulating their ideas and explicitly citing the theory they are using.

The coursework assignments allow the students to develop their problem-solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback; the summative assessment has a secondary formative purpose as well as its primary summative purpose.

Note: the exam for MAS8615 is more challenging than the exam for MAS3925.

General Notes

N/A