LARIS is a Python package for analyzing ligand-receptor interactions in spatial transcriptomics data. It identifies spatially-specific cell-cell communication patterns by integrating gene expression, spatial information, and cell type annotations.
- Spatial LR interaction strength: Calculate ligand-receptor interaction scores for each individual cell
- Spatial specificity: Identify LR pairs with significant spatial variable patterns
- Inference at cell type level: Compute sender-receiver cell type interaction scores
- Spatial neighborhoods: Analyze interactions in the context of spatial cell type neighborhoods
- Calibrated significance: exact p-values against an expression-matched null (gene pairs of matched abundance in the same sender-receiver context), with no permutation sampling; the FDR is controlled within each sender-receiver pair
- Cross-condition analysis: Compare interactions across conditions with subject-level statistics and two validated estimators
You could simply install LARIS via pip in your conda environment:
pip install larisFor the development version in GitHub, you could install via:
pip install git+https://github.com/genecell/LARIS.gitSince v0.12.0 LARIS ships compiled Rust kernels inside the wheel, so
pip install laris needs nothing extra. Building from source (a GitHub
install, or a platform without a wheel) additionally requires a Rust
toolchain: curl https://sh.rustup.rs -sSf | sh.
If LARIS is useful for your research, please consider citing M. Dai, T. Török, D. Sun, et al., LARIS enables accurate and efficient ligand and receptor interaction analysis in spatial transcriptomics, bioRxiv (2025).