Centre for Research Informatics Training
Spatial transcriptomics analysis
Event details
Sessions
- 2 November 2026 — 09:30 to 17:30 — eLearning (CCRIT)
- 9 November 2026 — 09:30 to 17:30 — eLearning (CCRIT)
- 16 November 2026 — 09:30 to 17:30 — eLearning (CCRIT)
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About the course
Spatial transcriptomics technologies make it possible to measure genome-wide gene expression while preserving the spatial organisation of cells and tissues. This course provides a practical introduction to analysing spatial transcriptomics data using the Seurat package in R and related tools.
Participants will learn how to process spatial transcriptomics datasets, perform quality control, normalisation, and data integration, and apply clustering and dimensionality reduction techniques. The course also covers visualisation of spatial gene expression patterns, identification of spatially variable features, and inference of cell-cell interactions.
By the end of the course, participants should be able to independently conduct and critically evaluate analyses of spatial transcriptomics experiments.
Teaching is primarily hands-on, with short presentations and demonstrations introducing the concepts and methods needed to analyse spatial transcriptomics data.
Intended audience
This course is suitable for:
- researchers and students interested in analysing spatial transcriptomics data
- participants who want practical experience with spatial transcriptomics analysis workflows
- researchers with experience of high-throughput sequencing who wish to extend their skills to spatially resolved transcriptomics
- 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
The following experience is recommended:
- analysis of bulk RNA-seq data
- analysis of single-cell RNA-seq data
- 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 |
| Cambridge University registered students non-attendance | £22.00 |
| Special events | Per event |
Payment options will be provided in booking confirmation emails sent after registration.
General information
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