escape.matrix: Calculate gene set enrichment scores

In ncborcherding/escape: Easy single cell analysis platform for enrichment

Calculate gene set enrichment scores

Description

This function allows users to input both the single-cell RNA-sequencing counts and output the enrichment scores as a matrix.

Usage

escape.matrix(
  input.data,
  gene.sets = NULL,
  method = "ssGSEA",
  groups = 1000,
  min.size = 5,
  normalize = FALSE,
  make.positive = FALSE,
  BPPARAM = SerialParam(),
  ...
)

Arguments

input.data	The count matrix, Seurat, or Single-Cell Experiment object.
gene.sets	Gene sets can be a list, output from getGeneSets, or the built-in gene sets in the escape package escape.gene.sets.
method	Select the method to calculate enrichment, AUCell, GSVA, ssGSEA or UCell.
groups	The number of cells to separate the enrichment calculation.
min.size	Minimum number of gene necessary to perform the enrichment calculation
normalize	Whether to divide the enrichment score by the number of genes TRUE or report unnormalized FALSE.
make.positive	During normalization shift enrichment values to a positive range TRUE for downstream analysis or not TRUE (default). Will only be applied if normalize = TRUE.
BPPARAM	A BiocParallel::bpparam() object that for parallelization.
...	pass arguments to AUCell GSVA, ssGSEA, or UCell call

Value

matrix of enrichment scores

Author(s)

Nick Borcherding, Jared Andrews

See Also

getGeneSets to collect gene sets.

Examples

GS <- list(Bcells = c("MS4A1", "CD79B", "CD79A", "IGH1", "IGH2"),
           Tcells = c("CD3E", "CD3D", "CD3G", "CD7","CD8A"))
pbmc_small <- SeuratObject::pbmc_small
ES <- escape.matrix(pbmc_small, 
                    gene.sets = GS, 
                    min.size = NULL)

ncborcherding/escape documentation built on Sept. 23, 2024, 10:01 p.m.