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Run Bootstrapped Metabolite Set Enrichment Analysis (MSEA)

Run_bootstrap_MSEA.Rd

This function performs bootstrapped metabolite set enrichment analysis on a given dataset. It ensures that the ranking conditions are set properly and conducts the enrichment analysis using either the KS-signed method or fgsea.

Usage

Run_bootstrap_MSEA(
  object,
  n_bootstraps = 50,
  min_pathway_size = 3,
  report_ambiguity_scores = F,
  boot_fract_cutoff = 0.5
)

Arguments

object

A S2IsoMEr object initialized by initEnrichment containing the necessary data and parameters, including annotations, annotation weights, rankings, pathway list, and additional settings.

n_bootstraps

An integer specifying the number of bootstrap samples to generate.

min_pathway_size

An integer specifying the minimum number of metabolites that must be present in a given term for it to be considered.

report_ambiguity_scores

A logical value indicating whether to calculate and report ambiguity scores for the annotations.

boot_fract_cutoff

A numeric value specifying the minimum fraction of bootstraps in which a pathway must appear to be considered in the final results.

Value

A list containing the results of the enrichment analysis, including:

  • summarized enrichment results

  • per-bootstrap enrichment results

  • the number of bootstraps

  • the fraction matched to the pathway

  • the comparison conditions

  • annotation ambiguity scores if calculated

Details

This function performs a bootstrapped metabolite set enrichment analysis by resampling the annotations and calculating enrichment scores for each bootstrap sample. It handles both KS-signed method or fgsea methods for enrichment analysis and returns a comprehensive summary of the results.

References

Korotkevich G, Sukhov V, Sergushichev A (2019). “Fast gene set enrichment analysis.” bioRxiv. doi:10.1101/060012, http://biorxiv.org/content/early/2016/06/20/060012.

Napoli F (2017). “signed-ks-test.” https://github.com/franapoli/signed-ks-test/blob/master/signed-ks-test.R.

Examples

if (FALSE) { # \dontrun{
data("example_MSEA_obj")
result <- Run_bootstrap_MSEA(object = example_MSEA_obj, n_bootstraps = 50)
} # }