Perform the enrichment analysis (over-representation) on the genes

Usage

RunEnrichment(
  srt = NULL,
  group.by = NULL,
  test.use = "wilcox",
  DE_threshold = "avg_log2FC > 0 & p_val_adj < 0.05",
  geneID = NULL,
  geneID_groups = NULL,
  geneID_exclude = NULL,
  IDtype = "symbol",
  result_IDtype = "symbol",
  backend = c("cpp", "r"),
  species = "Homo_sapiens",
  db = "GO_BP",
  db_update = FALSE,
  db_version = "latest",
  db_combine = FALSE,
  convert_species = TRUE,
  Ensembl_version = NULL,
  mirror = NULL,
  features = NULL,
  TERM2GENE = NULL,
  TERM2NAME = NULL,
  minGSSize = 10,
  maxGSSize = 500,
  unlimited_db = c("Chromosome", "GeneType", "TF", "Enzyme", "CSPA"),
  GO_simplify = FALSE,
  GO_simplify_cutoff = "p.adjust < 0.05",
  simplify_method = "Wang",
  simplify_similarityCutoff = 0.7,
  cores = 1,
  verbose = TRUE,
  ...
)

Arguments

srt: A Seurat object or SummarizedExperiment object containing the results of differential expression analysis (RunDEtest()). If specified, the genes and groups will be extracted from the object automatically. If not specified, the geneID and geneID_groups arguments must be provided.
group.by: Metadata column(s) used to color cells.
test.use: Test to be used in differential expression analysis. This argument is only used if srt is specified.
DE_threshold: Filter condition for differential expression analysis. This argument is only used if srt is specified.
geneID: Gene IDs.
geneID_groups: A factor vector specifying the group labels for each gene.
geneID_exclude: Gene IDs to be excluded from the analysis.
IDtype: Type of gene IDs in the srt object or geneID argument. This argument is used to convert the gene IDs to a different type if IDtype is different from result_IDtype.
result_IDtype: Desired type of gene ID to be used in the output. This argument is used to convert the gene IDs from IDtype to result_IDtype.
backend: Enrichment backend. "cpp" is the default and uses a fast native hypergeometric ORA implementation and returns the enrichment table without enrichResult objects. "r" uses clusterProfiler::enricher() and returns enrichResult objects in results. GO_simplify = TRUE currently uses the R backend.
species: "Homo_sapiens" or "Mus_musculus".
db: Annotation sources. One or more of "GO", "GO_BP", "GO_CC", "GO_MF", "KEGG", "WikiPathway", "Reactome", "CORUM", "MP", "DO", "HPO", "PFAM", "CSPA", "Surfaceome", "SPRomeDB", "VerSeDa", "TFLink", "hTFtarget", "TRRUST", "JASPAR", "ENCODE", "MSigDB", "CellTalk", "CellChat", "Chromosome", "GeneType", "Enzyme", "TF", "CytoTRACE2". MSigDB subcollections use "MSigDB_<collection>" (e.g. "MSigDB_H"). "CytoTRACE2" is species-independent and is required by RunCytoTRACE.
db_update: Force a refresh. FALSE loads the cache when available.
db_version: Database version to retrieve.
db_combine: Whether to combine multiple databases into one. If TRUE, all database specified by db will be combined as one named "Combined".
convert_species: Use a species-converted database when the annotation is missing for species.
Ensembl_version: Ensembl version. NULL uses the latest.
mirror: Specify an Ensembl mirror to connect to. The valid options here are "www", "uswest", "useast", "asia".
features: A named list of feature lists for custom enrichment gene sets. If provided, it takes precedence over TERM2GENE and db.
TERM2GENE: A data frame specifying the gene-term mapping for a custom database. The first column should contain the term IDs, and the second column should contain the gene IDs.
TERM2NAME: A data frame specifying the term-name mapping for a custom database. The first column should contain the term IDs, and the second column should contain the corresponding term names.
minGSSize: The minimum size of a gene set to be considered in the enrichment analysis.
maxGSSize: The maximum size of a gene set to be considered in the enrichment analysis.
unlimited_db: Names of databases that do not have size restrictions.
GO_simplify: Whether to simplify the GO terms. If TRUE, additional results with simplified GO terms will be returned.
GO_simplify_cutoff: Filter condition for simplification of GO terms. This argument is only used if GO_simplify is TRUE.
simplify_method: Method to be used for simplification of GO terms. This argument is only used if GO_simplify is TRUE.
simplify_similarityCutoff: The similarity cutoff for simplification of GO terms. This argument is only used if GO_simplify is TRUE.
cores: The number of worker processes to use for parallelization. Default is 1.
verbose: Whether to print the message. Default is TRUE.
...: Passed to helper functions.

Value

If input is a Seurat object, returns the modified Seurat object with the enrichment result stored in the tools slot.

If input is a geneID vector with or without geneID_groups, return the enrichment result directly.

Enrichment result is a list with the following component:

enrichment: A data.frame containing all enrichment results.
results: A list of enrichResult objects from the DOSE package.
geneMap: A data.frame containing the ID mapping table for input gene IDs.
input: A data.frame containing the input gene IDs and gene ID groups.
DE_threshold: A specific threshold for differential expression analysis (only returned if input is a Seurat object).

Examples

term2gene <- data.frame(
  Term = c(
    rep("Endocrine markers", 5),
    rep("Exocrine markers", 5),
    rep("Ductal markers", 5)
  ),
  symbol = c(
    "INS", "GCG", "SST", "IAPP", "PCSK1",
    "PRSS1", "CPA1", "CELA3A", "REG1A", "CTRB1",
    "KRT19", "SOX9", "MUC1", "CFTR", "KRT7"
  )
)
gene_groups <- rep(c("Cluster1", "Cluster2"), each = 6)
enrich_out <- RunEnrichment(
  geneID = c(
    "INS", "GCG", "SST", "IAPP", "PRSS1", "CPA1",
    "KRT19", "SOX9", "MUC1", "CFTR", "KRT7", "REG1A"
  ),
  geneID_groups = gene_groups,
  TERM2GENE = term2gene,
  minGSSize = 2
)
#> ℹ [2026-08-30 05:00:22] Start Enrichment analysis
EnrichmentPlot(
  res = enrich_out,
  db = "custom",
  plot_type = "comparison"
)

Perform the enrichment analysis (over-representation) on the genes

Usage

Arguments

Value

See also

Examples