- Sheffield - 17th December 2018
- 09:30am - 5pm
- The Diamond, Workroom 1
- 09:30 - 10:00 Introduction to RNA-seq and experimental design
- 10:00 - 12:30 Hands-on tutorial on RNA-seq data formats, QA and alignment
- 13:30 - 14:30 Differential Expression
- 14:30 - 16:30 Hands-on tutorial on gene set enrichment
Please leave us feedback on today’s course using this link
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 in R
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
Please download the Integrative Genomics Viewer (IGV) for your operating system using this link
- Mark Dunning, Bioinformatics Core Director
- Sokratis Kariotis, PhD Student, Wang lab
- Niamh Errington, PhD Student, Wang lab
Registration is open now