Abstract

Measuring gene expression on a genome-wide scale has become common practice over the last two decades or so, with microarrays predominantly used pre-2008. With the advent of next generation sequencing technology in 2008, an increasing number of scientists use this technology to measure and understand changes in gene expression in often complex systems. As sequencing costs have decreased, using RNA-Seq to simultaneously measure the expression of tens of thousands of genes for multiple samples has never been easier. The cost of these experiments has now moved from generating the data to storing and analysing it.

About This Material

This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.

Questions this will address

• What are the differentially expressed genes in the mammary gland of pregnant versus lactating mice?
• How to analyze RNA count data using limma-voom?
• How to perform quality control (QC) of RNA-seq count data?

Learning Objectives

• Analysis of RNA-seq count data using limma-voom
• QC of count data
• Visualisation and interactive exploration of count data
• Identification of differentially expressed genes