This repository contains all code to reproduce the results from the Multi-sample and Multi-modal integration study using SpatialLeiden
Müller-Bötticher, N., Malt, A., Kiessling, P., Eils, R., Kuppe, C., & Ishaque, N. (2026). Atlas-scale spatially aware clustering with support for 3D and multimodal data using SpatialLeiden. bioRxiv. https://doi.org/10.64898/2026.02.27.708246
When contributing to this repository please ensure that
- before you commit a notebook (ipynb) you remove all outputs to ensure that the file sizes and commits don't explode
- install pre-commit and run it when committing. This can be achieved with a git hook.
Just follow the documentation.
Conda environment configuration files (all .yml files) are available where needed (next to the files they belong to). The corresponding environment should mostly be clear from the (file)name or might be directly used within the code. Environments must be installed manually before executing the code i.e. via
conda env create -f {env}.ymlFurthermore, the CONDA_PATH in utils.py may need to be
adjusted according to your systems setup before running the notebooks.
The env_export directory contains the exact specifications of the environments generated by
conda env exportThese are meant to document the exact versions of the packages used rather than for installing.
All data necessary to reproduce the results can be downloaded by executing the scripts in the downloads directory. Note that some of them need their own environment.
Analysis can be reproduced by running the Jupyter Notebooks in the top-level
directory.
The notebooks analysing H&E datasets with lazyslide (VisiumHD-CRC) will require to be run in the 'lazyslide' conda environment,
all others can be run in the 'spatialleiden' environment.
time (v1.9) was installed via
mkdir -p ~/local/src
cd ~/local/src
wget https://ftp.gnu.org/gnu/time/time-1.9.tar.gz
tar -xzf time-1.9.tar.gz
cd time-1.9
./configure --prefix=$HOME/local
make
make install