This course will provide an introduction to the technology, data analysis, tools and resources used in RNA sequencing and transcriptomics. The content is intended to provide a broad overview of the subject area, and to introduce participants to simple data analysis using  the command line and APIs. It will also highlight key resources, approaches and methodologies to begin the biological interpretation and analysis of transcriptomics data. Topics will be delivered using a mixture of lectures, practical sessions and open discussions. Practical work during the course will use small, example data-sets - there will be no opportunity to  analyse personal data.

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 18 operating system and the R statistical packages. We recommend these free tutorials:



• 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?

Learning outcomes

After this course you should be able to:



• Describe a variety of applications and workflow approaches for NGS technologies

• Use a range of bioinformatics software and tools to undertake basic analysis of RNA-Seq data
• 
Evaluate the advantages and limitations of NGS analyses
• Interpret and annotate data with functional information using public resources

Course content

During this course you will learn about:



• RNA-Seq file formats and basics of experiemental design
• RNA-Seq bioinformatics workflow steps following sequence generation

• Methods for transcriptomics; QC, mapping, visualisation tools

• Data resources to assist in the functional analysis and interpretation of transcriptomic data
• Introduction to single-cell transcriptomics
• Data resources covered:
  • Expression Atlas
  • Open Targets Platform
  • RNAcentral
  • Rfam
  • Reactome

Trainers

Please read our page on application advice before starting your application. In order to be considered for a place on this course, you must do the following:

1. Complete the online application form
2. Submit a Microsoft Word (.docx) document containing three short paragraphs with a biography, work history and description of your current research interests; each paragraph should be no more than 100 words
3. Provide a letter of support from a supervisor or a senior co-worker explaining why you should be selected for this course

Please submit all documents to Marina Pujol (mpuljo@ebi.ac.uk)  by 12:00 GMT on Friday 4 October, 2019.

Incomplete applications will not be considered.