Biochemistry BSc/MSci

Bioinformatics and Data Analysis using R 4B option BIOL4297

  • Academic Session: 2023-24
  • School: School of Infection and Immunity
  • Credits: 20
  • Level: Level 4 (SCQF level 10)
  • Typically Offered: Semester 2
  • Available to Visiting Students: Yes

Short Description

This course will provide students with theory and extensive practice in data analysis and plotting in R. With a focus on Bioinformatics, but relevant to all biological datasets. It is suitable for students with no prior knowledge of bioinformatics or R.


This option is assigned to block S2-B. There is normally 3 hours of teaching on Tuesdays.




The course will be assessed by two multiple-choice quizzes (2x10%) and in-course assessment consisting of a mini-project report (80%).

Are reassessment opportunities available for all summative assessments? Not applicable for Honours courses

Reassessments are normally available for all courses, except those which contribute to the Honours classification. Where, exceptionally, reassessment on Honours courses is required to satisfy professional/accreditation requirements, only the overall course grade achieved at the first attempt will contribute to the Honours classification. For non-Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

Course Aims

The course will offer practical application of data analysis and visualisation in omic datasets with a focus on exploratory analysis and generation of plots and figures in R.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ Demonstrate best practice of coding in R, with particular focus on the manipulation of omic data files through statistical analysis, transformations, and plot generation;

■ Critically explore and communicate omic datasets using established bioinformatic visualisation techniques;

■ Critically interpret omic data results in terms of their biological meaning with reference to the experimental design.

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.