ora_bino: Over-representation analysis with binomial resampling...

In mseapca: Metabolite Set Enrichment Analysis for Loadings

Over-representation analysis with binomial resampling adjustment

Description

Performs ORA while adjusting for undetected metabolites by binomial resampling.

Usage

ora_bino(SIG, DET, M, method = "naive", probs = c(0.025, 0.975), nsim = 1000, lambda = 5)

Arguments

SIG	Character vector of significant metabolites.
DET	Character vector of detected metabolites.
M	Named list of metabolite sets.
method	"naive", "weighted", or "shrink".
probs	Quantiles for the confidence interval (default 95%).
nsim	Number of binomial simulations (default 1000).
lambda	Shrinkage parameter used when method = "shrink" (default: 5).

Value

A list containing one matrix. Rows = metabolite sets; columns = lower, median, and upper p-values.

Author(s)

Hiroyuki Yamamoto

Examples

# Example: Metabolome data
data(fasting_mseapca)

SIG <- fasting_mseapca$SIG
DET <- fasting_mseapca$DET
M <- fasting_mseapca$pathway

# Perform ORA using detected metabolites only
B <- ora_bino(SIG, DET, M, method="naive", nsim = 10)

B$`Range of p-values for each pathway`

mseapca documentation built on Aug. 8, 2025, 7:20 p.m.