Date: 16 - 19 March 2021

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.

Virtual course

Participants will learn via a mix of pre-recorded lectures, live presentations, and trainer Q&A sessions. Practical experience will be developed through group activities and trainer-led computational exercises. Live sessions will be delivered using Zoom with additional support and communication via Slack. 

Pre-recorded material will be made available to registered participants prior to the start of the course and in the week before the course, there will be a brief induction session. Computational practicals will run on EMBL-EBI's virtual training infrastructure, meaning participants will not require access to a powerful computer or install complex software on their own machines.

Participants will need to be available between the hours of 09:30-17:30 GMT each day of the course. Trainers will be available to assist, answer questions, and further explain the analysis during these times.

Keywords: Expression Atlas , Reactome pathways database , Gene expression (gene-expression), ArrayExpress Archive of Functional Genomics Data , RNAcentral

Target audience: 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.

Capacity: 30


Activity log