mseapca (version 2.2.1)

msea_ora_range: Wrapper function for Over-Representation Analysis with p-value range estimation

Description

This function performs over-representation analysis (ORA) to assess metabolite set enrichment while considering uncertainty due to undetected metabolites. It wraps different methods for estimating a p-value range, including full enumeration and binomial resampling.

Usage

msea_ora_range(SIG, DET = NULL, M,
               option = "ora_full",
               probs = c(0.025, 0.975),
               nsim = 1000,
               lambda = 5)

Value

A list containing a matrix with p-value range results for each metabolite set. Columns include lower, median, and upper p-values.

Arguments

SIG

A character vector of statistically significant metabolites.

DET

A character vector of all detected metabolites. Required for all methods except ora_full.

M

A named list of metabolite sets, each containing a character vector of metabolites.

option

Method to use for estimating the p-value range. One of "ora_full", "bino_naive", "bino_weighted", or "bino_shrink".

probs

Numeric vector of quantile probabilities for binomial simulation (e.g., c(0.025, 0.975)). Ignored for ora_full.

nsim

Number of simulations for binomial-based estimation. Ignored for ora_full.

lambda

Shrinkage parameter for "bino_shrink" option.

Author

Hiroyuki Yamamoto

Details

This wrapper function allows switching between multiple ORA implementations that estimate the uncertainty due to undetected metabolites. The ora_full method uses exhaustive enumeration of all possible detection patterns, while the other methods use binomial resampling with different estimation strategies (naive, weighted, or shrinkage-based).

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 <- msea_ora_range(SIG, DET, M, option = "bino_naive", nsim=10)

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