blisa identifies spatially enriched ligand-receptor (LR) interactions from spatial transcriptomics data using bivariate Local Moran's I (LISA) statistics. It bins cells into a hexagonal grid, computes the spatial co-enrichment of every ligand-receptor pair across bins, and flags "High-High" hotspot bins where both partners are co-expressed beyond chance. Results can be summarised at the ligand-receptor or pathway level and visualised as spatial maps and heatmaps of sender-receiver interactions.
Install the development version from GitHub:
library(devtools)
devtools::install_github("ChenLaboratory/blisa")Step-by-step case studies showing blisa in action. Browse the full list under the Vignettes tab, or start here:
- Exploring cell-cell interaction with blisa - the core workflow on an imaging-based (Xenium) breast cancer dataset: hex binning, LR hotspot detection, and sender-receiver interaction scoring.
- Visium profile of human breast tumour -
applying blisa to spot-based (Visium) data, including pathway-level
aggregation with
blisaPathway()and hotspots over the H&E image.