Recent technological advances have made it possible to obtain genome-wide transcriptome data from individual cells using high-throughput sequencing. This course provides a practical introduction to single-cell RNA sequencing (scRNA-seq) analysis.

Participants will gain hands-on experience with widely used software packages and methodologies for processing, analysing, and interpreting scRNA-seq data. Topics include data preprocessing, quality control, normalisation, dimensionality reduction, batch correction and data integration, cell clustering, and differential expression and abundance analysis.

By the end of the course, participants should be able to independently conduct and critically evaluate analyses of scRNA-seq experiments.

Teaching is primarily hands-on, with short presentations and demonstrations introducing the concepts and methods needed to analyse single-cell transcriptomic data.

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== Intended audience ==

This course is suitable for:

• researchers and students interested in analysing single-cell transcriptomic data
• participants who want practical experience with scRNA-seq analysis workflows
• researchers with experience of high-throughput sequencing who wish to extend their skills to single-cell data analysis
• participants with a working knowledge of UNIX and R

== Course fees ==

All fees are per full training day.

{| class="wikitable"
|-
! 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.

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