Single Cell RNAseq Workshop

Workshop materials for scRNAseq Analysis in R with Seurat, run by members of QCIF, SIH, Monash, and the Australian BioCommons. Topics covered include QC, normalisation, dimensionality reduction, batch correction (Harmony), clustering, cell type annotation (SingleR), and differential expression.

Visit the Workshop page.

Repository structure

Path	Description
part1/ and part2/	Workshop sections (*.Rmd files) that learners work through sequentially with follow-along and self-guided exercises
data/	Input datasets used during the workshop
scripts/	Helper and preprocessing scripts
setup/	Training environment (VM) setup files
_bookdown.yml, _output.yml, _common.R, etc.	Auxiliary files for rendering the bookdown site

Rendering the bookdown

install.packages(c("bookdown", "downlit", "pander")) # if required
Rscript -e 'rmarkdown::render("scripts/kang2018_preprocessing.Rmd")'
Rscript -e 'bookdown::render_book'

Output is written to docs/.

Environment setup

1. Install CRAN, bioconductor, and github packages:

bash setup/setup.sh install

Review any failed package installs and resolve manually in an interactive R session. Usually due to missing dependencies in the output log.

2. Move relevant files and folder structure for the VM.

For small files packaged with the repo:

bash setup/setup.sh prep_data

Transfer the rest from a local machine, stored on 2026-07 scRNAseq/data Google Drive:

rsync -vPrla *.qs2 tdevXX@XXX.XXX.XXX.XX:/home/tdevXX/data

3. Start up the rstudio server:

module load rstudio
sudo rstudio-server start

• Set a password if required

4. Open rstudio in the browser with the url provided from rstudio-server start.

5. Test everything is ready by running the workshop end-to-end

6. Move files and libraries to /etc/skel/

7. Clear the rstudio server session history before snapshotting and cloning:

sudo rm -rfv /etc/skel/.local/share/rstudio/session