Gain an introduction to the technology, data analysis, tools, and resources used in RNA sequencing and transcriptomics. The content will provide a broad overview of the subject area, and introduce participants to basic analysis of transcriptomics data using the command line. It will also highlight key public data repositories and methodologies that can be used to start the biological interpretation of expression data. Topics will be delivered using a mixture of lectures, practical exercises, and open discussions. Computational work during the course will use small, example data-sets, and there will be no opportunity to analyse personal data.
We plan to deliver this course in-person in our training suite at EMBL-EBI, Hinxton. Please be aware that we are continually evaluating the ongoing pandemic situation and, as such, may need to change the format of courses at short notice. Your safety is paramount to us; you can read our COVID guidance policy for more information. All information is correct at time of publishing.
Who is this course for?
This course is aimed at life science researchers wanting to learn more about processing RNA-seq data and later downstream analysis. It will help those wanting a basic introduction to handling RNA-seq data, guiding them through several common approaches that can be applied to their own datasets. It features taught and practical sessions that cover how to interpret gene expression data and learn more about the biological significance of certain results.
Participants will require a basic knowledge of the Unix command line, the Ubuntu 20 operating system, and the R statistical packages. Some basic tutorials that cover these tools are:
- Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix
- Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training
- Basic R concept tutorials: www.r-tutor.com/r-introduction
Regardless of your current knowledge, we encourage successful participants to use these, and other materials, to prepare for attending the course and future work in this area
What will I learn?
After the course you should be able to:
- Describe a variety of applications and workflow approaches for NGS technologies
- Apply bioinformatics software and tools to undertake analysis of RNA-seq data
- Evaluate the advantages and limitations of NGS analyses
- Interpret and annotate data with functional information using public resources
During this course you will learn about:
- RNA-seq file formats and basics of experimental design
- RNA-seq bioinformatics workflow steps following sequence generation
- Methods for transcriptomics; QC, mapping, and visualisation tools
- Data resources to assist in the functional analysis and interpretation of transcriptomic data
- Introduction to de novo approaches
- Introduction to single-cell transcriptomics
- Data resources covered: