run_CCI: Generate cell cell communication score

In SydneyBioX/scFeatures: scFeatures: Multi-view representations of single-cell and spatial data for disease outcome prediction

Generate cell cell communication score

Description

This function calculates the ligand receptor interaction score using SingleCellSignalR. The output features are in the form of celltype a -> celltype b – ligand 1 -> receptor 2 , which indicates the interaction between ligand 1 in celltype a and receptor 2 in celltype b.

It supports scRNA-seq.

Usage

run_CCI(data, type = "scrna", ncores = 1)

Arguments

data	A list object containing data matrix and celltype and sample vector.
type	input data type, either scrna, spatial_p, or spatial_t
ncores	number of cores

Value

a matrix of samples x features The features are in the form of ligand 1 receptor 2 celltype a, ligand 1 receptor 2 celltype b ... etc, with the numbers representing cell-cell interaction probability.

Examples

utils::data("example_scrnaseq" , package = "scFeatures")
data <- example_scrnaseq[1:1000, 1:100]
celltype <- data$celltype
sample <- data$sample
data <- as.matrix(data@assays$RNA@data)

alldata <- scFeatures:::formatData(data = data, celltype = celltype, sample = sample )
feature_CCI <- run_CCI(alldata, type = "scrna" ,  ncores = 1 )

SydneyBioX/scFeatures documentation built on March 13, 2024, 12:36 a.m.