holistOmics {STATegRa} | R Documentation |
This function is defunct. Use omicsNPC instead.
holistOmics(dataInput, dataTypes, comb.method = c("Fisher", "Liptak", "Tippett"), numPerm = 1000, numCores = 1, verbose = FALSE)
dataInput |
List of ExpressionSet objects, one for each data modality. |
dataTypes |
Character vector with possible values: 'RNA-seq', 'microarray' |
comb.method |
Character vector with possible values: 'Fisher', 'Liptak', 'Tippett', if more than one is specified, all will be used. |
numPerm |
Number of permutations |
numCores |
Number of CPU cores to use |
verbose |
Logical, if set to TRUE holistOmics prints out the step that it performs |
A data.frame
Nestoras Karathanasis
Pesarin, Fortunato, and Luigi Salmaso. Permutation tests for complex data: theory, applications and software. John Wiley & Sons, 2010.
# Load the data data("TCGA_BRCA_Batch_93") # Setting dataTypes, the first two ExpressionSets include RNAseq data, # the third ExpressionSet includes Microarray data. dataTypes <- c("RNAseq", "RNAseq", "Microarray") # Setting methods to combine pvalues comb.method = c("Fisher", "Liptak", "Tippett") # Setting number of permutations numPerm = 1000 # Setting number of cores numCores = 1 # Setting holistOmics to print out the steps that it performs. verbose = TRUE # Run holistOmics analysis. # The output is a data.frame of p-values. # Each row corresponds to a gene name. Each column corresponds to a method # used in the analysis. ## Not run: out <- holistOmics(dataInput = TCGA_BRCA_Data, dataTypes = dataTypes, comb.method = comb.method, numPerm = numPerm, numCores = numCores, verbose = verbose) ## End(Not run)