RNA-seq Analysis for Beginners

Course Materials (final)

Around 1.5 hours of pre-recorded lectures will be made available the week before the course

Overview

Please note that we will provide some pre-recording lecture material (around 1.5 hours) for you to watch before the workshop. The workshop itself will be hands-on; working through exercises and watching demonstrations from the lecturers.

High-throughput RNA-sequencing is now the standard technique for quantifying transcript abundance in a biological sample of interest. In this course we will describe the processes that take place once you submit a library for RNA sequencing, and what data you should expect to receive from the Bioinformatics Core.

We will describe the steps involved to go from sequencing library to a list of genes that show statistically significant differences between your biological conditions of interest. Practical sessions will use the user-friendly Galaxy interface (https://usegalaxy.org/) to demonstrate tasks such as alignment, quality control and assessing differential expression. We will also showcase some web sites you can use for enrichment and pathways analysis.

Please note that the course will not cover the analysis of RNA-seq data using the R programming langugage

Who should attend this course?

Researchers in life sciences who want to get an appreciation for the computational steps involved in RNA-seq analysis, but not neccesarily wishing to execute the pipeline for themselves.

Objectives:- After this course you should be able to:

  • Appreciate some of the issues that can arise when designing an RNA-seq experiment
  • Recall the key pipeline steps in an RNA-seq analysis
  • Understand the contents of fastq and bam file format for RNA-seq data
  • Perform a gene set enrichment analysis using available online tools

Aims:- During this course you will learn about:

  • Basic principles of Experimental design for RNA-seq experiments
  • The steps in a best-practice pipeline for RNA-seq analysis
  • The theory behind popular methods for pathways and gene set enrichment analysis
  • Executing basic Bioinformatics tools using Galaxy

Software installation

Please download the Integrative Genomics Viewer (IGV) for your operating system using this link

Instructors

  • Mark Dunning, Bioinformatics Core Director
  • Dennis Wang, Lecturer and Group Leader in Genomic Medicine and Bioinformatics
  • Johnathan Cooper-Knock, NIHR Clinical Lecturer (pre-recorded material only)
  • Emily Chambers, Bioinformatics Core Analyst
  • Sokratis Kariotis, PhD Student, Wang lab

Course Data

Registration

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