Introduction to Omics and R BIOL5360
- Academic Session: 2022-23
- School: School of Infection and Immunity
- Credits: 20
- Level: Level 5 (SCQF level 11)
- Typically Offered: Semester 2
- Available to Visiting Students: No
This course will provide students with a critical understanding of a range of modern omics technologies and their applications. This will include the practical application of bioinformatic data analysis, with a focus on programming in R.
This course is made up of lectures, tutorials, and computing laboratory sessions.
50 % group presentation of 10-15 minutes marked on slide deck, presentation, and Q&A session (ILOs 1& 5)
50 % R set exercise- includes submission of script file, plots, and interpretation of results (approx. 500 words) (ILOs 2,3, & 4)
The aims of this course are to provide students with:
■ A deep understanding of omics approaches; their molecular basis, the tools and technologies used for analysing omic data, as well as advantages and challenges of said approaches compared to conventional target analysis.
■ The skills to design an omics experiment and analyse the data output using R programming, with common packages and statistical analysis to provide a foundation understanding for future project and industry placements.
Intended Learning Outcomes of Course
By the end of this course students will be able to:
1. Critically discuss and evaluate omics technologies and techniques involved in data collection and validation
2. Manipulate omic data files through statistical analysis, transformations, and plot generation, demonstrating best practice of coding in R.
3. Critically interpret omic data results in terms of their biological meaning with reference to the experimental design.
4. Critically explore and communicate findings from omic datasets using established bioinformatic visualisation techniques
5. Design an experimental strategy to exploit omics analysis and critically discuss the importance of controls.
Minimum Requirement for Award of Credits
Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.