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DO.enrichR

Source: R/utils_functions.R
DO.enrichR.Rd

Performs Gene Ontology enrichment analysis on differentially expressed genes using the EnrichR API. Separately analyzes upregulated and downregulated genes and returns results.

Usage

DO.enrichR(
  df_DGE,
  gene_column,
  pval_column,
  log2fc_column,
  pval_cutoff = 0.05,
  log2fc_cutoff = 0.25,
  path = NULL,
  filename = "",
  species = "Human",
  go_catgs = c("GO_Molecular_Function_2023", "GO_Cellular_Component_2023",
    "GO_Biological_Process_2023")
)

Arguments

df_DGE

data.frame containing differential gene expression results.

gene_column

column name in df with gene symbols.

pval_column

column name in df with p-values.

log2fc_column

column name in df with log2 fold changes.

pval_cutoff

adjusted p-value threshold for significance (default = 0.05).

log2fc_cutoff

log2 fold change threshold for up/down regulation (default = 0.25).

path

folder path where the output Excel file will be saved. A subfolder "GSA_Tables" will be created.

filename

suffix used in the Excel filename (e.g., "GSA_CellType_MyAnalysis.xlsx").

species

species name for enrichment analysis. Options include "Human", "Mouse", "Yeast", etc. (default = "Mouse").

go_catgs

GO databases to use. Defaults to c("GO_Molecular_Function_2023", "GO_Cellular_Component_2023", "GO_Biological_Process_2023").

Value

data.frame with GO enrichment results if path is NULL, otherwise writes an Excel file.

Examples

library(enrichR)

sce_data <- readRDS(system.file("extdata", "sce_data.rds", package = "DOtools"))
DGE_result <- DO.MultiDGE(sce_data,
                         sample_col = "orig.ident",
                         method_sc = "wilcox",
                         annotation_col = "annotation",
                         ident_ctrl = "healthy")
#> Centering and scaling data matrix
#> 2025-07-26 09:22:51 - Corrected annotation names in pseudo-bulk object by replacing '-' with '_'.
#> 2025-07-26 09:22:51 - Starting DGE single cell method analysis
#> 2025-07-26 09:22:51 - Comparing disease with healthy in: Monocytes
#> 2025-07-26 09:22:51 - Skipping Monocytes since one comparison has fewer than 3 cells!
#> 2025-07-26 09:22:51 - Comparing disease with healthy in: CD4_T_cells
#> 2025-07-26 09:22:51 - Comparing disease with healthy in: NK
#> 2025-07-26 09:22:51 - Comparing disease with healthy in: CD8_T_cells
#> 2025-07-26 09:22:51 - Skipping CD8_T_cells since one comparison has fewer than 3 cells!
#> 2025-07-26 09:22:51 - Comparing disease with healthy in: B_cells
#> 2025-07-26 09:22:51 - Comparing disease with healthy in: pDC
#> 2025-07-26 09:22:51 - Finished DGE single cell method analysis
#> 2025-07-26 09:22:51 - Starting DGE pseudo bulk method analysis
#> 2025-07-26 09:22:51 - Comparing disease with healthy in: B_cells
#> 2025-07-26 09:22:51 - Skipping B_cells since one comparison has fewer than 3 cells!
#> 2025-07-26 09:22:51 - Comparing disease with healthy in: CD4_T_cells
#> 2025-07-26 09:22:51 - Skipping CD4_T_cells since one comparison has fewer than 3 cells!
#> 2025-07-26 09:22:51 - Comparing disease with healthy in: Monocytes
#> 2025-07-26 09:22:51 - Skipping Monocytes since one comparison has fewer than 3 cells!
#> 2025-07-26 09:22:51 - Comparing disease with healthy in: NK
#> 2025-07-26 09:22:51 - Skipping NK since one comparison has fewer than 3 cells!
#> 2025-07-26 09:22:51 - Comparing disease with healthy in: pDC
#> 2025-07-26 09:22:51 - Skipping pDC since one comparison has fewer than 3 cells!
#> 2025-07-26 09:22:51 - Comparing disease with healthy in: CD8_T_cells
#> 2025-07-26 09:22:51 - Skipping CD8_T_cells since one comparison has fewer than 3 cells!
#> 2025-07-26 09:22:51 - Finished DGE pseudo bulk method analysis
#> 2025-07-26 09:22:51 - DGE pseudo bulk result is empty...

DGE_result <- DGE_result[DGE_result$celltype == "CD4_T_cells",]

result_GO <- DO.enrichR(df_DGE = DGE_result,
                       gene_column = "gene",
                       pval_column = "p_val_SC_wilcox",
                       log2fc_column = "avg_log2FC_SC_wilcox",
                       pval_cutoff = 0.05,
                       log2fc_cutoff = 0.25,
                       path = NULL,
                       filename = "",
                       species = "Human",
                       go_catgs = "GO_Biological_Process_2023")
#> Connection changed to https://maayanlab.cloud/Enrichr/
#> Connection is Live!
#> Uploading data to Enrichr... Done.
#>   Querying GO_Biological_Process_2023... Done.
#> Parsing results... Done.
#> Uploading data to Enrichr... Done.
#>   Querying GO_Biological_Process_2023... Done.
#> Parsing results... Done.