FluidGMGenes: Gene selection using Random Forest only.

In bvnlab/SCATTome: FluidgmR

Description

Uses node purity based importance ordering of genes to select important genes.

Usage

FluidGMGenes(train, ColumnThreshold, RowThreshold)

Arguments

train
ColumnThreshold
RowThreshold

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (train, ColumnThreshold, RowThreshold) 
{
    source("Fluidigm.r")
    dtrain = read.table(train, sep = ",", header = TRUE, fill = TRUE, 
        as.is = TRUE)
    ct <- checkData(dtrain, Type = "Train")
    if (ct == 1) {
        d3 <- ExcludeData(dtrain, ColumnThreshold = 0.5, RowThreshold = 0.5, 
            Type = "Train")
    }
    d4 <- MultImpute(d3$Data, Type = "Train")
    d5 <- MultImpute(d4, Type = "Train")
    d5 <- na.omit(d5)
    d6 <- ScaleCenterTrain(d5)
    d7 <- FeatureSelection(d6$Data)
    d8 <- FeatureSelectionLasso(d6$Data)
    write.table(c("GeneListObject"), "GeneListObject.txt", quote = FALSE, 
        row.names = FALSE, col.names = FALSE)
    write.csv(d6$Data, "TrainDataMod.csv", quote = FALSE, row.names = FALSE)
    write.csv(cbind(d6$Mean, d6$SD), "TrainMeanSD.csv", quote = FALSE, 
        row.names = FALSE)
    write.csv(d7$ImportantGenes, "RandomForestgeneList.csv", 
        quote = FALSE, row.names = FALSE)
    write.csv(d8, "LASSOgeneList.csv", quote = FALSE, row.names = FALSE)
    return(list(Index = "GeneListObject", TrainData = d6$Data, 
        CenterMean = d6$Mean, CenterSD = d6$SD, ImportantGeneList = d7$ImportantGenes, 
        LassoGenes = d8))
  }

bvnlab/SCATTome documentation built on May 13, 2019, 9:05 a.m.