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

• How to convert RNA-seq reads into counts?
• How to perform quality control (QC) of RNA-seq reads?
• How to do this analysis efficiently in Galaxy?

Learning Objectives

• Learn how RNA-seq reads are converted into counts
• Understand QC steps that can be performed on RNA-seq reads
• Generate interactive reports to summarise QC information with MultiQC
• Use the Galaxy Rule-based Uploader to import FASTQs from URLs
• Make use of Galaxy Collections for a tidy analysis
• Create a Galaxy Workflow that converts RNA-seq reads into counts