pARIgene {pARI} | R Documentation |
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, ...)
Arguments
X |
Data matrix where rows represent the |
pathways |
List of pathways where names indicates the name of the pathway. |
alpha |
Numeric value in '[0,1]'. |
family |
String character. Name of the family confidence envelope to compute the critical vector
from |
delta |
Numeric value. |
B |
Numeric value. Number of permutations, default to 1000. |
test.type |
Character string. Choose a type of tests among |
complete |
Boolean value. If |
iterative |
Boolean value. If |
approx |
Boolean value. Default to |
ncomb |
Numeric value. If |
step.down |
Boolean value. Default to |
max.step |
Numeric value. Default to 10. Maximum number of steps for the step down approach, so useful when |
... |
Further arguments |
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.
Author(s)
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:
Andreella, A., Hemerik, J., Finos, L., Weeda, W., & Goeman, J. (2023). Permutation-based true discovery proportions for functional magnetic resonance imaging cluster analysis. Statistics in Medicine, 42(14), 2311-2340.
See Also
The type of tests implemented: signTest
permTest
.