msea_ora_range {mseapca} | R Documentation |
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)
Arguments
SIG |
A character vector of statistically significant metabolites. |
DET |
A character vector of all detected metabolites. Required for all methods except |
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 |
probs |
Numeric vector of quantile probabilities for binomial simulation (e.g., |
nsim |
Number of simulations for binomial-based estimation. Ignored for |
lambda |
Shrinkage parameter for |
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).
Value
A list containing a matrix with p-value range results for each metabolite set. Columns include 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$pathway
# Perform ORA using detected metabolites only
B <- msea_ora_range(SIG, DET, M, option = "bino_naive", nsim=10)
B$`Range of p-values for each pathway`