SpatialTis is an ultra-fast spatial analysis toolkit for large-scale spatial single-cell data.
- ✔️ Spatial Transcriptome (Non single-cell)
- ✔️ Spatial Proteome (Single-cell)
- 🦀 Core algorithms implements in Rust
- 🚀 Parallel processing support
- Cell neighbors search (KD-Tree/R-Tree/Delaunay)
- Cell-Cell Interaction
- Marker spatial co-expression
- Spatial variable genes (current support: SOMDE)
- GCNG: Inferring ligand-receptor using graph convolution network
- Identify neighbor dependent markers
- Spatial distribution
- Hotspot detection
- Spatial auto-correlation
- Spatial heterogeneity
SpatialTis requires Python >= 3.8.
pip install spatialtis
# For full features
pip install 'spatialtis[all]'
Install the current development version
pip install git+https://github.com/Mr-Milk/SpatialTis.git
docker pull mrmilk/spatialtis
To start a docker container:
cd your/data/
docker run -it --rm -p 8888:8888 -v "${PWD}:/analysis" spatialtis
-it
: Run the container in interactive mode-rm
: Clean file system in container after shutting down- If local port 8888 is taken, try
-p 9999:8888
and change to 9999. -v
: Mount your data directory to the working directory/analysis
in the container.${PWD}
is the directory where you run this command. All changes made in this directory will be saved.
If you are interested in using low level algorithms yourself, Please refer to spatialtis_core It provides clear document for all exposed API.