collapseRowsUsingKME | R Documentation |
This function selects only the most informative probe for each gene in a kME table, only keeping the probe which has the highest kME with respect to any module in the module membership matrix. This function is a special case of the function collapseRows.
collapseRowsUsingKME(MM, Gin, Pin = NULL, kMEcols = 1:dim(MM)[2])
MM |
A module membership (kME) table with at least a subset of the columns corresponding to kME values. |
Gin |
Genes labels in a 1 to 1 correspondence with the rows of MM. |
Pin |
If NULL (default), rownames of MM are assumed to be probe IDs. If entered, Pin must be the same length as Gin and correspond to probe IDs for MM. |
kMEcols |
A numeric vector showing which columns in MM correspond to kME values. The default is all of them. |
datETcollapsed |
A numeric matrix with the same columns as the input matrix MM, but with rows corresponding to the genes rather than the probes. |
group2row |
A matrix whose rows correspond to the unique gene labels and whose 2 columns report which gene label (first column called group) is represented by what probe (second column called selectedRowID) |
selectedRow |
A logical vector whose components are TRUE for probes selected as representatives and FALSE otherwise. It has the same length as the vector Pin. |
Jeremy Miller
collapseRows
# Example: first simulate some data
set.seed(100)
ME.A = sample(1:100,50); ME.B = sample(1:100,50)
ME.C = sample(1:100,50); ME.D = sample(1:100,50)
ME1 = data.frame(ME.A, ME.B, ME.C, ME.D)
simDatA = simulateDatExpr(ME1,1000,c(0.2,0.1,0.08,0.05,0.3), signed=TRUE)
simDatB = simulateDatExpr(ME1,1000,c(0.2,0.1,0.08,0.05,0.3), signed=TRUE)
Gin = c(colnames(simDatA$datExpr),colnames(simDatB$datExpr))
Pin = paste("Probe",1:length(Gin),sep=".")
datExpr = cbind(simDatA$datExpr, simDatB$datExpr)
MM = corAndPvalue(datExpr,ME1)$cor
# Now run the function and see some example output
results = collapseRowsUsingKME(MM, Gin, Pin)
head(results$MMcollapsed)
head(results$group2Row)
head(results$selectedRow)
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