Chapter 1 Overview

In Computer Lab 7B, we introduce some Bioinformatics terminology that may be foreign. If this is the case, we recommend that you read over sections 2.1 to 2.3 of this supplement. This will also give you a head start on your readings for Computer Lab 8B.

In Computer Lab 8B, our focus is on using R to conduct a small gene expression analysis.

1.1 Learning Objectives

By the end of these labs, you will have learnt how to:

  • Download and use Bioconductor R packages for Bioinformatics (Computer Lab 8B)
  • Use edgeR to normalise gene count data (Computer Lab 8B)
  • Conduct a differential gene expression analysis (Computer Lab 8B)
  • Perform FWER and FDR correction on p-values (Computer Lab 7B)
  • Create volcano plots to visualise differential gene expression (Computer Lab 8B)

Don’t worry if this sounds unachievable right now. Some prior knowledge of biology and genomics would be helpful, but is not required - we discuss all the relevant terminology in brief in this supplement!

Gene expression analyses can be quite complicated. We will take our time and go step-by-step. We won’t focus on all the underlying mathematics (which is a little beyond the scope of this subject), so much as on the general R analysis process. We are not expecting you to become an expert bioinformatician within this short time-frame, but we do hope that this exposure to the world of Bioinformatics sparks interest.