Single cell omics provides the opportunity to elucidate the heterogeneity within tissues and cultures through omic approaches at the level of a single cell. It is therefore ideal for a precision approach in multiple fields, such as biomedical or cancer sciences. In this course you will learn about single cell omics approaches, as well as having the opportunity to analyse data yourself. This course is designed for individuals with some previous R experience, but no high level of expertise is required.

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

Introduction to Next Generation Sequencing Bioinformatics (BIOL5346)

BIOL5354

1. R Script file containing the analysis (40 %) [ILO 1] 

2. Individual presentation (13 mins) (60 %) [ILO 2 & 3] 

This course aims to provide students with the tools to analyse, visualise, and interpret single cell omic data using the R programming language. Students will have the opportunity to build their R skills while expanding their knowledge of this cutting-edge field of bioinformatics.

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

1. Demonstrate best practice of intermediate coding in R, with particular focus on the manipulation of single cell omic data files through parsing, transformations, and plot generation;

2. Explore and evaluate single cell omic data and effectively communicate the findings using appropriate bioinformatic visualisation techniques

3. Formulate appropriate hypotheses relating to the underlying biology from the results of a single cell omics experiment

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.