Data Exploration and Interpretation for Bioinformatics BIOL5379

  • Academic Session: 2023-24
  • School: School of Infection and Immunity
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No

Short Description

This course will provide bioinformatics students with an introduction to and practice in bioinformatic data exploration and visualisation with a focus on programming in R.

Timetable

This course consists of lectures and computing practicals in semester 2.

Requirements of Entry

none

Excluded Courses

BIOL 5354 Bioinformatics using R for biologists

Co-requisites

N/A

Assessment

The course will be assessed entirely by coursework assessment (100%).

The assessment will comprise 2 components:

■ a set exercise component involving analysis of a dataset (70%) [ILOs 1,2]

■ a report of 750 words involving interpretation of the analysis of this dataset (30%) [ILO 3]

Course Aims

This course aims to foster extensive, critical and integrative understanding and development of practical skills in relation to bioinformatic data exploration and visualisation. The course will introduce the basics of data visualisation in omic datasets with a focus on exploratory analysis and generation of omic plots and figures in R. It will also provide practice in using these methods. Understanding and skills in this core aspect of bioinformatics expertise will provide a foundation and help prepare students for projects in this area and for employment within the bioinformatics sector.

Intended Learning Outcomes of Course

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

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

2. Critically explore and communicate omic datasets using established bioinformatic visualisation techniques

3. Critical interpretation of 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.