In this workshop, you will learn how to analyse single-cell RNA-seq count data using Seurat. This workshop uses the 10X Genomics dataset from Pal et al. 2021, from which we will consider five samples from human normal sorted epithelial population. This workshop includes the following three parts:

  • Standard analysis of one sample
  • Integration analysis of multiple samples
  • Differential expression analysis using pseudo-bulk

The detailed material can be found here.


The course is aimed at PhD students, Master’s students, and third & fourth year undergraduate students. Some basic R knowledge is assumed - this is not an introduction to R course. If you are not familiar with the R statistical programming language it is compulsory that you work through an introductory R course before you attend this workshop.

R packages used

The following R packages will be used:

  • Seurat
  • edgeR
  • vcd
  • scales
  • pheatmap

Time outline

Activity Time
Introduction & setup 10m
Part 1. Standard analysis 35m
Part 2. Integration analysis 35m
Part 3. Pseudo-bulk DE analysis 30m
Q & A 10m

Workshop goals and objectives

Learning goals

  • Learn the standard scRNA-seq analysis pipeline.
  • Understand the process of single cell integration analysis.
  • Understand the biological variation between samples in single cell experiments and how to account for it.

Learning objectives

  • Perform a standard analysis of a single 10X scRNA-seq sample.
  • Perform an integration analysis of multiple 10X scRNA-seq samples.
  • Apply the pseudo-bulk approach to DE analysis.

Workshop package installation


This is necessary in order to reproduce the code shown in the workshop. The workshop is designed for R 4.1 and can be installed using one of the two ways below.

Via Docker image

If you’re familiar with Docker you could use the Docker image which has all the software pre-configured to the correct versions.

docker run -e PASSWORD=abc -p 8787:8787 yunshun/singlecellworkshop:latest

Once running, navigate to http://localhost:8787/ and then login with Username:rstudio and Password:abc.

You should see the Rmarkdown file with all the workshop code which you can run.