Run Metabolite/Lipids enrichment analysis for single cell metabolomics

Run_enrichment() A wrapper to run either ORA or MSEA based on the initialized enrichment object

Usage

Run_enrichment(
  object,
  Run_DE = FALSE,
  DE_pval_cutoff = 0.05,
  DE_LFC_cutoff = 1,
  min.pct.diff = 0.1,
  ...
)

Arguments

object: A numeric matrix of n metabolites (rows) and m cells or measurments (columns).
Run_DE: A logical indicating whether to run differential analysis using limma's rank Sum Test With Correlation. Ignored if enrichment type is 'MSEA'.
DE_pval_cutoff: A numeric indicating p-value cutoff. Default is 0.05.
DE_LFC_cutoff: A numeric indicating the minimum log2 fold change for differential analysis
min.pct.diff: A numeric indicating the minimum percentage difference between samples/cells in both conditions for a marker to be considered differentially abundant.
...: Additional arguments passed to functions used internally, such as Run_bootstrap_ORA, Run_simple_ORA, Run_bootstrap_MSEA, and Run_simple_MSEA. Consult the specific function documentation for details on these arguments.

Value

Data.frame with enrichment results

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
)
} # }