View source: R/miRNAPrioritization.R
| prioritizeMicroRNA | R Documentation | 
Outputs a table of miRNA ordered with respective p-values derived from method for prioritization
prioritizeMicroRNA( enriches0, pathClust, method = "AggInv", methodThresh = NULL, enrichmentFDR = 0.25, topClust = 2, sampRate = 1000, outDir = ".", dataDir = ".", saveSampling = TRUE, runJackKnife = TRUE, saveJackKnife = FALSE, numCores = 1, saveCSV = TRUE, prefix = "", autoSeed = TRUE )
enriches0 | 
 miRNA-pathway enrichment dataset obtained from miRNAPathwayEnrichment.  | 
pathClust | 
 Pathway clusters, obtained from MappingPathwaysClusters.  | 
method | 
 Vector of methods pCut, AggInv, AggLog, sumz, sumlog.  | 
methodThresh | 
 Vector of methods threshold for each method in method, if NULL use default thresh values in method.  | 
enrichmentFDR | 
 FDR cut-off calculating miRNA-pathway hits in the input cluster based on significant enrichment readouts.  | 
topClust | 
 Top x clusters to perform miRNA prioritization on.  | 
sampRate | 
 Sampling rate for CLT.  | 
outDir | 
 Output directory.  | 
dataDir | 
 Data directory.  | 
saveSampling | 
 If TRUE, saves sampling data as RDS for each cluster in topClust in dataDir.  | 
runJackKnife | 
 If TRUE, jacknifing will be performed.  | 
saveJackKnife | 
 If TRUE, saves jack-knifed sampling data as RDS for each cluster in topClust in dataDir.  | 
numCores | 
 Number of CPU cores to use, must be at least one.  | 
saveCSV | 
 If TRUE, saves CSV file for each cluster in topClust in outDir.  | 
prefix | 
 Prefix for all saved data.  | 
autoSeed | 
 random permutations are generated based on predetermined seeds. TRUE will give identical results in different runs.  | 
Table of miRNA and p-values, each row contains a miRNA and its associated p-values from the methods.
data("miniTestsPanomiR")
prioritizeMicroRNA(enriches0 = miniTestsPanomiR$miniEnrich,
   pathClust = miniTestsPanomiR$miniPathClusts$Clustering,
   topClust = 1,
   sampRate = 50,
   method = c("aggInv"),
   saveSampling = FALSE,
   runJackKnife = FALSE,
   numCores = 1,
   saveCSV = FALSE)
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