Step: KEGG Enrichment Analysis on Differentially Expressed Variables

Perform KEGG enrichment analysis on differentially expressed variables using glyfun::enrich_ora_kegg().

This step requires dea_res (differential analysis result from DEA). Run one of step_dea_limma(), step_dea_ttest(), or step_dea_wilcox() before this step. Only execute for glycoproteomics experiments with exactly 2 groups. If used for glycomics experiments, the step will be skipped. Use all genes in OrgDb as the background.

Usage

step_sig_enrich_kegg(
  universe = "all",
  plot_type = "dotplot",
  plot_width = 7,
  plot_height = 7,
  ...
)

Arguments

universe: The universe (background) to use for enrichment analysis. One of "all" (all genes in OrgDb), "detected" (detected variables in exp).
plot_type: Plot type for enrichment results ("dotplot", "barplot", etc.).
plot_width: Width of the plot in inches. Default is 7.
plot_height: Height of the plot in inches. Default is 7.
...: Additional arguments passed to glyfun::enrich_ora_kegg().

Value

A glysmith_step object.

Details

Data required:

exp: The experiment to perform KEGG enrichment analysis for
dea_res: The result from DEA, generated by step_dea_xxx().

Tables generated:

kegg_enrich: A table containing the KEGG enrichment results.

AI Prompt

This section is for AI in inquire_blueprint() only.

Include this step by default if DEA is performed on glycoproteomics data.
Leave universe to "all" (by default) unless the user explicitly mentions that the background should be the detected variables in exp.
If the experiment has more than 2 groups but the user wants enrichment for a specific two-group comparison, ask which two groups to compare and include step_subset_groups(groups = c("A", "B")) before DEA and enrichment steps.

Examples

step_sig_enrich_kegg()
#> <step "step_sig_enrich_kegg()"> KEGG enrichment analysis
step_sig_enrich_kegg(plot_type = "barplot")
#> <step "step_sig_enrich_kegg(plot_type = \"barplot\")"> KEGG enrichment analysis