normGenesetExpression: Calculate normalized expression of a gene set

In fmicompbio/swissknife: Handy code shared in the FMI CompBio group

Calculate normalized expression of a gene set

Description

Calculate normalized expression for a set of genes in each cell from a SingleCellExperiment, using random sets of similarly expressed genes as background to account for cell quality and sequencing depth.

Usage

normGenesetExpression(
  sce,
  genes,
  expr_values = "logcounts",
  subset.row = NULL,
  R = 200,
  nbins = 100,
  BPPARAM = SerialParam()
)

Arguments

sce	SingleCellExperiment object.
genes	character vector with the genes in the set. Must be a subset of rownames(sce).
expr_values	Integer scalar or string indicating which assay of sce contains the expression values.
subset.row	Sample random genes only from these. If NULL (the default), the function will sample from all genes in sce. Alternatively, subset.row can be a logical, integer or character vector indicating the rows (genes) of sce to use for sampling. This allows for example to exclude highly variable genes from the sampling which are likely expressed only in certain cell types.
R	Integer scalar giving the number of random gene sets to sample for normalization.
nbins	Integer scalar, specifying the number of bins to group the average expression levels into before sampling (passed to sampleControlElements). Higher numbers of bins will increase the match to the target distribution(s), but may fail if there are few elements to sample from.
BPPARAM	An optional BiocParallelParam instance determining the parallel back-end to be used during evaluation.

Value

A numeric vector with normalized gene set scores for each cell in sce.

Author(s)

Michael Stadler

Examples

if (require(SingleCellExperiment)) {
    # get sce
    example(SingleCellExperiment, echo=FALSE)
    rownames(sce) <- paste0("g", seq.int(nrow(sce)))
    
    # calculate gene set expression scores
    markers <- c("g1", "g13", "g27")
    scores <- normGenesetExpression(sce, markers, R = 50)
    
    # compare expression of marker genes with scores
    plotdat <- cbind(scores, t(logcounts(sce)[markers, ]))
    cor(plotdat)
    pairs(plotdat)
}

fmicompbio/swissknife documentation built on June 11, 2025, 4:17 p.m.