Analysis of Spatial Transcriptomics Data (Visium HD)

Welcome to our hands-on workbook collection to learn spatial transcriptomics data analysis, with a focus on 10x Genomics Visium HD data!

Spatial transcriptomics allows us to measure gene expression across tissue sections while preserving spatial information, helping us understand not just what genes are active, but where they are active.

With our workbooks, you will explore how to analyze spatial transcriptomics data using R and RStudio. Whether you're new to spatial data or already familiar with single-cell workflows, our guides will walk you through the essential steps.

Table of contents

• Workbooks overview
• Credits
• Contributions
• Citation
• Quick Start

Workbooks overview 📘

Our workbooks cover:

• Learn how to load spatial data into R and examine how the data is structured
• Key steps in the analysis workflow, including quality control, preprocessing, clustering and visualisation, cluster annotation, spatial clustering, and integration with single-cell transcriptomics data.

Credits 👥

The workbooks are being written by Katrin Sameith and Andreas Petzold at the DRESDEN-concept Genome Center.

Contributions 🤝

We welcome contributions! To contribute:

• Create your own fork of the GitHub repository
• Submit a pull request once your edits are complete
• Please include clear descriptions of your changes and make sure your code runs

Citation

If you used our workbooks to analyze your data, please cite it by mentioning the DRESDEN-concept Genome Center URL "https://genomecenter.tu-dresden.de".

Quick Start 🚀

On a linux laptop, you need to install singularity first and then you can get started right away using our containerized environment:

# Clone the repository
git clone git@github.com:dcgc-bfx/2025-ngs-cn-summer-school.git

# Container image
SINGULARITY_IMAGE=oras://gcr.hrz.tu-chemnitz.de/dcgc-bfx/singularity/singularity-single-cell:v1.6.5

# Set user, password and port
export SINGULARITYENV_RSTUDIO_USER=$(whoami)
export SINGULARITYENV_RSTUDIO_PASSWORD="verysecret"
export SINGULARITYENV_RSTUDIO_PORT=9999

# Define temporary directory
workdir=...
mkdir -p ${workdir}/singularity ${workdir}/tmp ${workdir}/rserver

# Start R-Server
singularity exec \
  --cleanenv \
  --scratch /run,/var/lib/rstudio-server \
  --workdir ${workdir}/singularity \
  --bind ${workdir}/tmp \
  --bind ${workdir}/rserver \
  ${SINGULARITY_IMAGE} \
  micromamba run --name single-cell /usr/lib/rstudio-server/bin/rserver --server-user=${SINGULARITYENV_RSTUDIO_USER} --www-port=${SINGULARITYENV_RSTUDIO_PORT}

Once you have started Rstudio with our container, you can start your analysis.

• Open your web browser (we recommend Chrome or Firefox).
• Navigate to:
  • localhost:${SINGULARITYENV_RSTUDIO_PORT}
• Log in with the credentials:
  • Username: ${SINGULARITYENV_RSTUDIO_USER}
  • Password: ${SINGULARITYENV_RSTUDIO_PASSWORD}
• Download required datasets with the datasets/download.R script
• Open workbooks/read_dataset_to_seurat.qmd

You're now ready to explore the workbooks in a fully configured RStudio environment!

Happy coding & exploring spatial data!