pARIgene: Permutation-based All-Resolutions Inference for Gene Expression Data

Description

This function computes the lower bound for the number of true discoveries within each cluster (pathways) of Gene Expression Data.

Usage

pARIgene(X= NULL, pathways, alpha = 0.05, family = "simes", delta = 0, 
B = 1000, test.type = "one_sample", complete = FALSE, iterative = FALSE, 
approx = TRUE, ncomb = 100, step.down = FALSE, max.step = 10, ...)

Value

by default returns a list with the following objects:

discoveries: lower bound for the number of true discoveries in the set selected
ix: selected variables

If complete = TRUE the raw pvalues and cv critical vector are also returned.

Arguments

X: Data matrix where rows represent the \(m\) variables and columns the \(n\) observations.
pathways: List of pathways where names indicates the name of the pathway.
alpha: Numeric value in `[0,1]`. \(\alpha\) level to control the family-wise error rate. Default to 0.05.
family: String character. Name of the family confidence envelope to compute the critical vector from "simes", "aorc", "beta", "higher.criticism", and "power". Default to "simes".
delta: Numeric value. \(\delta\) value. Please see the reference below. Default to 0.
B: Numeric value. Number of permutations, default to 1000.
test.type: Character string. Choose a type of tests among "one_sample", i.e., one-sample t-tests, or "two_samples", i.e., two-samples t-tests. Default "one_sample".
complete: Boolean value. If TRUE the sets of critical vectors and the raw \(p\)-values are returned. Default to FALSE.
iterative: Boolean value. If iterative = TRUE, the iterative method is applied (computationally demanding). Default to FALSE. Please see the reference below.
approx: Boolean value. Default to TRUE. If you are analyzing high dimensional data, we suggest to put approx = TRUE to speed up the computation time. Please see the reference below.
ncomb: Numeric value. If approx = TRUE, you must decide how many random sub collections (level of approximation) considered. Default to 100.
step.down: Boolean value. Default to FALSE If you want to compute the lambda calibration parameter using the step-down approach put TRUE. Please see the reference below.
max.step: Numeric value. Default to 10. Maximum number of steps for the step down approach, so useful when step.down = TRUE.
...: Further arguments

Author

Angela Andreella

References

For the general framework of All-Resolutions Inference see:

Goeman, Jelle J., and Aldo Solari. "Multiple testing for exploratory research. " Statistical Science 26.4 (2011): 584-597.

For permutation-based All-Resolutions Inference see: