runGSEA: Compute gene set enrichment

In theMILOlab/SPATA2: A Toolbox for Spatial Expression Analysis

Compute gene set enrichment

Description

Computes gene set enrichment based on the results of runDEA(). See details for more.

Usage

runGSEA(
  object,
  across,
  methods_de = "wilcox",
  max_adj_pval = 0.05,
  min_lfc = 0,
  n_highest_lfc = NULL,
  n_lowest_pval = NULL,
  signatures = NULL,
  test = c("hypergeometric", "kstest"),
  absolute = FALSE,
  background = 20000,
  power = 1,
  pval = 0.05,
  fdr = 0.05,
  reduce = TRUE,
  quiet = TRUE,
  chr_to_fct = TRUE,
  assay_name = activeAssay(object),
  verbose = NULL,
  ...
)

Arguments

object	An object of class SPATA2 or, in case of S4 generics, objects of classes for which a method has been defined.
across	Character vector. All grouping variables of interest.
methods_de	Character vector. All differential expression methods of interest.
max_adj_pval	Numeric value. Sets the threshold for adjusted p-values. All genes with adjusted p-values above that threshold are ignored.
min_lfc	Numeric value. Sets the threshold for average log fold change. All genes with an average log fold change below that threshold are ignored.
n_highest_lfc	Numeric value. Affects the total number of genes that are kept. See details.
n_lowest_pval	Numeric value. Affects the total number of genes that are kept. See details.
signatures	Character vector of signature names that are taken from the assays stored signatures. Defaults to all signatures of the currently active assay.
test	Choose an enrichment type e.g. c("hypergeometric", "kstest")
absolute	Takes max-min score rather than the max deviation from null (kstest only)
background	Size or character vector of background population genes
power	Exponent for weights (kstest only)
pval	Filter results to be less than pval cutoff
fdr	Filter results to be less than fdr cutoff
reduce	Logical value. If set to TRUE (the default) the return value of hypeR::hypeR() is reduced to what is necessary for SPATA2s function to work. If FALSE, the complete objects are stored. This will grow the SPATA2 object's size quickly!
quiet	Use true to suppress logs and warnings
assay_name	Only relevant if the SPATA2 object contains more than one assay: Denotes the assay of interest and thus the molecular modality to use. Defaults to the active assay as set by activateAssay().
verbose	Logical. If TRUE, informative messages regarding the computational progress will be printed. (Warning messages will always be printed.)
...	Additional arguments given to Seurat::FindAllMarkers()
gene_set_list	A named list of character vectors. Names of slots correspond to the gene set names. The slot contains the genes of the gene sets.Holds priority over gene_set_names.

Details

Computes gene set enrichment analysis using hypeR::hypeR(). It does so by iterating about all possible combinations of across and methods_de. Combinations for which no DE-results are found are silently skipped.

Value

The updated input object, containing the added, removed or computed results.

Examples

library(SPATA2)

data("example_data")

object <- example_data$object_UKF269T_diet

# requires the results of runDEA(object, across = "histology")!
object <- runDEA(object, across = "histology")

object <- runGSEA(object, across = "histology")

plotGseaDotplot(object, across = "histology", )

theMILOlab/SPATA2 documentation built on June 1, 2025, 9:11 p.m.