laris 0.9.0

LARIS enables accurate and efficient ligand and receptor interaction analysis in spatial transcriptomics

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.

Features

• Spatial LR interaction strength: Calculate ligand-receptor interaction scores using spatial adjacency information
• 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

📦 Installation

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

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

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

pip install laris

Quick Start

import laris as la
import scanpy as sc
import pandas as pd

# Load your spatial transcriptomics data
adata = sc.read_h5ad('spatial_data.h5ad')

# Define ligand-receptor pairs
lr_df = pd.DataFrame({
    'ligand': ['Tgfb1', 'Vegfa', 'Cxcl12'],
    'receptor': ['Tgfbr1', 'Kdr', 'Cxcr4']
})

# Step 1: Calculate LR integration scores
lr_adata = la.tl.prepareLRInteraction(
    adata, 
    lr_df,
    number_nearest_neighbors=15,
    use_rep_spatial='X_spatial'
)

# Step 2: Identify spatially-specific LR interactions and infer the LR interaction at cell type level
laris_results, celltype_results = la.tl.runLARIS(
    lr_adata,
    adata,
    n_nearest_neighbors=15,
    n_repeats=100,
    n_top_lr=1000,
    by_celltype=True,
    groupby='cell_type'
)

# View top spatially-specific LR pairs
print(laris_results.head(10))

# View top cell type-specific interactions
print(celltype_results.head(10))

# Filter for specific cell type pairs
endothelial_to_tumor = celltype_results[
    (celltype_results['sending_celltype'] == 'Endothelial') &
    (celltype_results['receiving_celltype'] == 'Tumor')
]
print(endothelial_to_tumor.head(10))