| pARIgene | R Documentation | 
This function computes the lower bound for the number of true discoveries within each cluster (pathways) of Gene Expression Data.
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, ...)
| 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 | 
by default returns a list with the following objects:
lower bound for the number of true discoveries in the set selected
selected variables
If complete = TRUE the raw pvalues and cv critical vector are also returned.
Angela Andreella
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.
The type of tests implemented: signTest permTest.
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