plotCCIspatial: Spatial map of dominant sender-receiver cell-type pairs at...
In blisa: Infer Cell-Cell Communication from Spatial Transcriptomics

plotCCIspatial

R Documentation

Spatial map of dominant sender-receiver cell-type pairs at BLISA hotspots

Description

For a selected ligand-receptor pair, identifies the dominant interacting cell-type pair at each significant hotspot bin and draws a spatial map of the tissue coloured by those pairs. Receiver cells are those inside hotspot bins; sender cells are drawn from the neighbouring bins defined by the LR pair's signalling mode.

Usage

plotCCIspatial(
  x,
  counts_by_group,
  index = 1,
  ligand = NULL,
  receptor = NULL,
  top_pairs = 30,
  weighted = TRUE
)

Arguments

`x`	A `blisa` object as returned by `blisa`.
`counts_by_group`	Named list of gene-by-bin count matrices, one per cell type. Typically the `counts_by_group` element returned by `hexBinCells`. Names must match the cell-type levels.
`index`	Integer. Row index into `x$LR_results` selecting the ligand-receptor pair to visualise. Ignored when both `ligand` and `receptor` are supplied. Default `1` (top-ranked pair).
`ligand`	Character. Ligand gene symbol. When both `ligand` and `receptor` are provided the matching LR pair is located automatically and `index` is ignored. Must be supplied together with `receptor`.
`receptor`	Character. Receptor gene symbol. Must be supplied together with `ligand`.
`top_pairs`	Integer. Maximum number of distinct cell-type pairs to show in the legend; remaining pairs are grouped as `"rare pairs"`. Default `30`.
`weighted`	Logical. If `TRUE` (default), the ligand contribution of each sender cell type at hotspot `h` is `\sum_{j \in N(h)} w_{hj} L_j`, using the same neighbours and row-standardised spatial weights as the bivariate Moran's I test (the hotspot bin itself is excluded). If `FALSE`, ligand counts are summed without weights over the hotspot bin and its neighbours.

Value

A ggplot object.

Examples

## Not run: 
# Continuing from the blisa() example:
# result <- blisa(spe, bin_size = 50, group = "cell_type")
binned <- hexBinCells(
  as.data.frame(SpatialExperiment::spatialCoords(spe)),
  SummarizedExperiment::assay(spe, "counts"),
  bin_size = 50, group = spe$cell_type
)
plotCCIspatial(result, binned$counts_by_group, index = 1)

## End(Not run)

blisa documentation built on Oct. 30, 2026, 9:10 a.m.