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Dot Plot for Over-Representation Analysis (ORA) Results

dotplot_ORA.Rd

This function creates a dot plot for ORA results, with options to color the dots by enrichment score or significance and to facet by a specified variable.

Usage

dotplot_ORA(
  ORA_res,
  alpha_cutoff = 0.05,
  color_by = "Significance",
  facet_by = NULL
)

Arguments

ORA_res

A data frame containing the ORA results from either filtered results in output of Run_bootstrap_ORA or direct output of Run_simple_ORA.

alpha_cutoff

A numeric value specifying the alpha cutoff for significance. Default is 0.05.

color_by

A character string indicating whether to color the dots by "Enrichment_score" or "Significance"

facet_by

An optional character string specifying a column name by which to facet the plot.

Value

A ggplot object displaying the dot plot of ORA results.

Details

The function creates a dot plot where the size of the dots represents the size of the term (e.g., number of true positives), and the color represents either the enrichment score or the significance (-log10 of the p-value). If multiple conditions are present, the plot is adjusted accordingly. The plot can also be faceted by a specified variable.

Examples

if (FALSE) { # \dontrun{
data("example_ORA_obj")
data("example_ORA_custom_universe")
input_scm = example_ORA_obj$scmatrix
conds = example_ORA_obj$conditions
cond_x = "U"
cond_y = "F"
ORA_obj <- initEnrichment(
  scmatrix = input_scm,
  conditions = conds,
  enrichment_type = "ORA",
  annot_db = "HMDB",
  consider_isomers = TRUE,
  consider_isobars = TRUE,
  polarization_mode = "positive",
  background_type = "sub_class",
  molecule_type = "Metabo",
  condition.x = cond_x,
  condition.y = cond_y
)
ORA_res <- Run_enrichment(
  object = ORA_obj,
  custom_universe = example_ORA_custom_universe,
  report_ambiguity_scores = TRUE,
  DE_LFC_cutoff = 0,
  min.pct.diff = 0
)
multi_cond_res = collapse_ORA_boot_multi_cond(ORA_boot_res_list = ORA_res)
p = dotplot_ORA(ORA_res = multi_cond_res$clean_enrich_res)
} # }