Applied Genomics

Module Aims: This module aims to provide the understanding, specialist knowledge and practical skills required to analyse large genomic datasets to answer questions about the genetic contribution to human health and disease.

Module Learning Outcomes:

By the end of the module students should be able to:

1. Understand how high-throughput sequencing (HTS) data are generated, and the related quality control processes
2. Analyse and interpret HTS data using command-line programming and bioinformatic approaches
3. Use appropriate publicly available resources to annotate and interpret genetic variation
4. Critically appraise published analyses of large genomic datasets
5. Appropriately apply different bioinformatic and statistical approaches in the context of common and rare diseases/traits

Pre-requisites:
Understanding of: the DNA structure, transcription and translation; different types of genetic variation and their functional effects; common vs rare variants; inheritance patterns; linkage disequilibrium and haplotypes. Ideally students would have completed the Genetic Epidemiology module, or at least attended “Introduction to genetic variation”, “LD, haplotypes and imputation”, and “Prioritising causal genes/variants” sessions.
The practical aspect of this module will involve linux-based command-line software, and it is expected that students have completed linux training and are comfortable with writing commands. Students are encouraged to refresh their linux skills, perhaps by working through some of the many online tutorials (e.g. https://tutorials.ubuntu.com/tutorial/command-line-for-beginners#0; http://www.ee.surrey.ac.uk/Teaching/Unix/index.html). Note that all necessary commands will be provided in the practical sessions.

Teaching Strategy:

Students are required to do 2-3 hours preparatory work for each session (self-directed learning). The sessions are a mixture of interactive lectures/workshops/group discussions used to consolidate and expand the knowledge gained during the preparatory work (e.g. through a group quiz), and hands-on genomic data analysis practicals. Each session will end with a 5-10min primer for the following session and the associated preparatory material. The module will use only publicly available resources, databases and software.

Assessment:

Group presentation, 50%: Groups of 3 or 4 students work on a project and make a presentation on a selected research topic during the last session. The presentation consists of each student introducing their own contribution, and the group drawing these together to explain how their work has addressed the overall task. Group marks are given for the content of the overall presentation, answering the research question and responding to questions during a 10-minute Q&A session following the presentation. For the overall presentation mark, 50% is based on the average of the marks given by other students on the module, and 50% is awarded by the module leader or a similarly qualified assessor appointed by them.

Individual technical report, 50%: Each student submits a 1000-word technical report on their group project a week after the end of the module. The report will include a brief introduction to the context and methods used, as well as detailed results and their interpretation.

Module Length: 4 days