Centre for Research Informatics Training
Bulk RNA-seq analysis
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Event details
Sessions
- 17 November 2026 — 09:30 to 17:00 — Craik-Marshall
- 24 November 2026 — 09:30 to 17:00 — Craik-Marshall
- 1 December 2026 — 09:30 to 17:00 — Craik-Marshall
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About the course
RNA sequencing (RNA-seq) is widely used to quantify gene expression and investigate biological processes at the transcriptome level. This course provides a practical introduction to the analysis of bulk RNA-seq data, from raw sequencing reads through to biological interpretation of differential expression results.
Participants will learn about quality control, alignment, and quantification of gene expression against a reference transcriptome. The course also covers exploratory data analysis in R using techniques such as principal component analysis and clustering, as well as differential expression analysis using the DESeq2 R/Bioconductor package. In addition, participants will learn how to generate visualisations, including heatmaps, and perform gene set testing to relate differentially expressed genes to biological functions and pathways.
By the end of the course, participants should be able to independently analyse bulk RNA-seq data and critically interpret the results.
Teaching is primarily hands-on, with short presentations and demonstrations introducing the concepts and methods needed to analyse bulk RNA-seq datasets.
Intended audience
This course is suitable for:
- researchers and students interested in analysing bulk RNA-seq data
- participants who want practical experience with transcriptomics data analysis workflows
- researchers with experience of high-throughput sequencing who wish to develop skills in RNA-seq data analysis
- participants with a working knowledge of UNIX and R
Prerequisites
Participants should have:
- a basic understanding of high-throughput sequencing technologies
- a working knowledge of the UNIX command line
- a working knowledge of R
For an overview of high-throughput sequencing technologies, we recommend watching this iBiology video.
The following experience is recommended:
- running analyses on High Performance Computing (HPC) clusters
Course fees
All fees are per full training day
| Category | Fee |
|---|---|
| Industry full charge | £130.00 |
| Academic / Government / charity concessionary | £65.00 |
| Cambridge University staff members / postdocs / visitors | £65.00 |
| Cambridge University registered students | Free |
| Special events | Per event |
Payment options will be provided in booking confirmation emails sent after registration.