Please note: there may be some adjustments to the teaching arrangements published in the course catalogue for 2020-21. Given current circumstances related to the Covid-19 pandemic it is anticipated that some usual arrangements for teaching on campus will be modified to ensure the safety and wellbeing of students and staff on campus; further adjustments may also be necessary, or beneficial, during the course of the academic year as national requirements relating to management of the pandemic are revised.

Bioinformatics using R for Biologists BIOL5354

  • Academic Session: 2021-22
  • School: Infection Immunity and Inflammation
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No
  • Available to Erasmus Students: No

Short Description

This course will provide life sciences students with an introduction and practice in bioinformatic data analysis with a focus on programming in R.


This course consists of lectures, tutorials and computer cluster tutorials in semester 2.

Requirements of Entry


Excluded Courses





Analysis of dataset- 80%

Written assignment- 20%

Course Aims

This course aims to introduce students to bioinformatic data processing with a focus on R programming, using a common package and statistical analysis. This course will introduce the basics of cleaning data and the general qualities of small/big, and low/high dimensional data. This course will provide practice in using these methods 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. Demonstrate fundamental principles of coding in R, with particular focus on manipulating large files, statistical analysis and generating plots.

2. Demonstrate a critical awareness of how omic and clinical datasets are generated, processed, quality controlled, cleaned and corrected.

3. Critically explore and communicate the biological results from big and high dimensional datasets using statistics and visualisation techniques appropriate to their own field.

4. Critically appraise omic and/or clinical data of a type that is now ubiquitous in biological research. 

5. Critically assess the role of bioinformatics in their own field.

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.