LARIS

Ligand And Receptor Interaction in Spatial transcriptomics data

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.

Feature

• 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, with no permutation sampling
• Cross-condition analysis: Compare interactions across conditions with subject-level statistics and two validated estimators

Documentation

LARIS documentation

LARIS tutorials

Datasets for LARIS tutorial

Installation

You could simply install LARIS via pip in your conda environment:

pip install laris

For the development version in GitHub, you could install via:

pip install git+https://github.com/genecell/LARIS.git

Since 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.

Citation

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).