computeCommunProbPathway: Compute the communication probability on signaling pathway...

In sqjin/CellChat: Inference and analysis of cell-cell communication from single-cell and spatial transcriptomics data

Compute the communication probability on signaling pathway level by summarizing all related ligands/receptors

Description

Compute the communication probability on signaling pathway level by summarizing all related ligands/receptors

Usage

computeCommunProbPathway(
  object = NULL,
  net = NULL,
  pairLR.use = NULL,
  thresh = 0.05
)

Arguments

object	CellChat object
net	A list from object@net; If net = NULL, net = object@net
pairLR.use	A dataframe giving the ligand-receptor interactions; If pairLR.use = NULL, pairLR.use = object@LR$LRsig
thresh	threshold of the p-value for determining significant interaction

Value

A CellChat object with updated slot 'netP':

object@netP$prob is the communication probability array on signaling pathway level; USER can convert this array to a data frame using the function 'reshape2::melt()',

e.g., 'df.netP <- reshape2::melt(object@netP$prob, value.name = "prob"); colnames(df.netP)[1:3] <- c("source","target","pathway_name")' or access all significant interactions using the function subsetCommunication

object@netP$pathways list all the signaling pathways with significant communications.

From version >= 1.1.0, pathways are ordered based on the total communication probabilities. NB: pathways with small total communication probabilities might be also very important since they might be specifically activated between only few cell types.

sqjin/CellChat documentation built on Nov. 10, 2023, 4:29 a.m.