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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