scTHI_score: scTHI_score

In miccec/scTHI: Indentification of significantly activated ligand-receptor interactions across clusters of cells from single-cell RNA sequencing data

scTHI_score

Description

This function allows the user to compute a score for a set of ligand-receptor pairs, from a single cell gene expression matrix, and detect specific Tumor-Host interactions. You must specify at least two clusters of cells (for example tumor cells and immune cells).

Usage

scTHI_score(expMat, cellCusterA, cellCusterB, cellCusterAName,
  cellCusterBName, topRank = 10, autocrineEffect = TRUE,
  fileNameBase = "scTHI", filterCutoff = 0.5, PValue = TRUE,
  pvalueCutoff = 0.05, nPermu = 1000, ncore = 8)

Arguments

expMat	ScRNA-seq gene expression matrix where rows are genes presented with Hugo Symbols and columns are cells. Gene expression values should be counts or normalized counts.
cellCusterA	Vector of columns of expMat that belong to the first cluster.
cellCusterB	Vector of columns of expMat that belong to the second cluster.
cellCusterAName	A character string labeling the clusterA.
cellCusterBName	A character string labeling the clusterB.
topRank	Filter threshold. Set to 10 (default) means that each gene of the interaction pair will be considered as expressed in a cell if it's in the top rank 10 percent.
autocrineEffect	if TRUE remove the paracrine filter
fileNameBase	Project name.
filterCutoff	Score threshold (default is 0.50). For each interaction pair, if the score calculated (for the partnerA or partnerB) will be less than filterCutoff the interaction pair will be discarded.
PValue	Logical, set to TRUE (default) compute statistical iterations. If p.value < 0.05, the value will be returned.
pvalueCutoff	cutoff of the p-value
nPermu	Number of iterations to perform (default is 1000).
ncore	Number of processors to use.

Value

A list of results, with four items: result (data.frame), expMat (matrix), clusterA (character), clusterA (character)

Examples

####################### example of scTHI_score
library(scTHI.data)
data(scExample)
result <-  scTHI_score(scExample,
      cellCusterA = colnames(scExample)[1:30],
      cellCusterB = colnames(scExample)[31:100],
      cellCusterAName = "ClusterA",
      cellCusterBName = "ClusterB", filterCutoff = 0,
     pvalueCutoff = 1, nPermu = 100, ncore = 8)

miccec/scTHI documentation built on April 21, 2023, 12:40 p.m.