This function calculates the pairwise distance between cell types for a sample by using the coordinates and cell types of the cells. We find the nearest neighbours of each cell and the cell types of these neighbours. These are considered as spatial interaction pairs. The cell type composition of the spatial interaction pairs are used as features. The function supports spatial proteomics and spatial transcriptomics.
Arguments
- data
A list object containing
datamatrix andcelltypeandsamplevector.- type
The type of dataset, either "scrna", "spatial_t", or "spatial_p".
- ncores
Number of cores for parallel processing.
Value
a dataframe of samples x features The features are in the form of protein 1 vs protein 2, protein 1 vs protein 3 ... etc, with the numbers representing the proportion of each interaction pairs in a give sample.
Examples
utils::data("example_scrnaseq" , package = "scFeatures")
data <- example_scrnaseq[1:50, 1:20]
celltype <- data$celltype
data <- data@assays$RNA@data
sample <- sample( c("patient1", "patient2", "patient3"), ncol(data) , replace= TRUE )
x <- sample(1:100, ncol(data) , replace = TRUE)
y <- sample(1:100, ncol(data) , replace = TRUE)
spatialCoords <- list( x , y)
alldata <- scFeatures:::formatData(data = data, sample = sample, celltype = celltype,
spatialCoords = spatialCoords )
feature_celltype_interaction <- run_celltype_interaction(
alldata, type = "spatial_p", ncores = 1
)