2024/25 Taught Postgraduate Module Catalogue
EPIB5032M Introduction to Genetic Epidemiology
15 creditsClass Size: 30
Module manager: Dr Mark Iles
Email: m.m.iles@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2024/25
Pre-requisite qualifications
Please be aware that students need a first degree in a quantitative/scientific subject with substantial maths/stats/numerical component (and at least a 2:1) – work experience (>2 years) in a similar quantitative field will be counted equivalently. A strong basic knowledge of stats is assumed (e.g. hypothesis testing, regression analysis, experience of data analysis using statistical software) – we do not teach core statistical concepts so you will struggle if you do not have these. We also assume that students know the basics of R prior to the course. You'll need to confirm this before I can approve you taking the module.English language requirements
An overall score of 7.0 on IELTS (International English Language Testing System) with at least 6.0 in writing and no other skill below 6.5.
This module is approved as an Elective
Module summary
This module will provide an introduction to genetic epidemiology covering all the main topics of current interest in the field. An introduction to human genetics will be included, but the main emphasis is on understanding statistical and epidemiological aspects of the study of the genetic basis of human diseases.Objectives
The objectives of this module are to:- introduce the core concepts and methods of genetic epidemiology;
- develop a basic understanding of human genetics and population genetics;
- introduce the different stages in understanding the genetic epidemiology of a disease including the study of familial aggregation, mapping disease genes and characterising their effect on disease risk;
- enable the student to understand the study designs and statistical methods appropriate to each of these stages;
- develop awareness of recent and ongoing developments in the study of genetic epidemiology, including technological advances and on-line resources.
Learning outcomes
By the end of this module the student should be able to:
- describe the basic concepts of human genetics including Mendelian laws of inheritance and recombination;
- describe patterns of genetic variation in populations and define key concepts such as linkage disequilibrium;
- describe how familial aggregation can be used to assess the importance of genes in determining disease risk;
- describe the principles behind linkage analysis, both parametric and non-parametric;
- describe the principles behind genetic association analysis;
- describe the advantages and disadvantages of family-based association studies;
- understand the statistical methods for carrying out linkage analysis, association analysis and family-based association analyses and demonstrate this understanding by carrying out simple analyses;
- describe the conduct of genome-wide association studies, including their strengths and limitations and issues surrounding multiple testing;
- describe emerging types of genetic information such as copy number variation and sequence data and understand the statistical approaches to their analysis;
- demonstrate some awareness of the genetic epidemiological literature, including an ability to critically read research papers in this field.
Skills outcomes
Students will acquire or consolidate skills in statistical analysis, and will learn how to apply these to the analysis of genetic association and linkage studies and to the investigation of familial aggregation.
Syllabus
The course will cover the following subjects:
- basic human genetics;
- basic population genetics;
- familial aggregation of disease;
- parametric linkage analysis;
- non-parametric linkage analysis;
- genetic association;
- candidate gene association studies;
- genome-wide association studies;
- family-based association studies;
- newer types of genetic information (such as copy number and sequence data);
- case studies of the genetic epidemiology of particular diseases.
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Presentation | 1 | 2.00 | 2.00 |
| Lecture | 6 | 2.00 | 12.00 |
| Practical | 2 | 2.00 | 4.00 |
| Seminar | 3 | 2.00 | 6.00 |
| Private study hours | 126.00 | ||
| Total Contact hours | 24.00 | ||
| Total hours (100hr per 10 credits) | 150.00 | ||
Private study
The private study will include guided reading (using text books and research papers), practical exercises and an in-depth case study of a particular multifactorial disease.Opportunities for Formative Feedback
This will be done by:- student attendance and contribution to lectures and tutorials;
- written assignments, one of which will be half way through the semester.
Methods of assessment
Coursework
| Assessment type | Notes | % of formal assessment |
| Essay | 3,000 word limit | 50.00 |
| Oral Presentation | Presentation of work in essay | 0.00 |
| Assignment | Short answer questions, Analytical work | 0.00 |
| Total percentage (Assessment Coursework) | 50.00 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Exams
| Exam type | Exam duration | % of formal assessment |
| Online Time-Limited assessment | 1 hr 30 mins | 50.00 |
| Total percentage (Assessment Exams) | 50.00 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Reading list
The reading list is available from the Library websiteLast updated: 29/04/2024 16:13:56
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- Undergraduate module catalogue
- Taught Postgraduate module catalogue
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