R/WritesigFeature.R

In pijush1285/sigFeature: sigFeature: Significant feature selection using SVM-RFE & t-statistic

#########################################################################
## Name:        WritesigFeature.R
## Author:      Pijush Das, Dr. Susanta Roychudhury, Dr. Sucheta Tripathy
##
##
## Change Log:
##   * April 4, 2018
##       - split sigFeature.R into several files for easier readability
##         and maintenance
#########################################################################

#########################################################################
## WritesigFeature(): This function will write the output data produced
## from the function sigFeatureRanking.enfold().
##
##
#########################################################################


WritesigFeature <-  function(results, x,  fileName="Result"){


    #Checking for the user variable.
    stopifnot(!is.null(x) == TRUE)
    stopifnot(is.list(results) == TRUE, length(results) > 0)


    wb = createWorkbook()
    for(i in seq_len(length(results))){
        label = paste("Iteration_",i)
        SelectedGene <- results[[i]]$feature.ids
        FeatureName <- colnames(x[,SelectedGene])
        l <- list(FeatureID=results[[i]]$feature.ids,
                FeatureName=FeatureName,
                TrainSampleID=results[[i]]$train.data.ids,
                TrainSampleLabels=results[[i]]$train.data.level,
                TestSampleID=results[[i]]$test.data.ids,
                TestSampleLabels=results[[i]]$test.data.level )
        n <- max(unlist(apply(l, length)))
        ll <- lapply(l, function(X) {c(as.character(X),
                rep("", times = n - length(X)))})
        out <- do.call(cbind, ll)
        out = data.frame(out)
        addWorksheet(wb, sheetName=label)
        writeDataTable(wb, i, x = out)
    }
    saveWorkbook(wb, paste(fileName,".xlsx", sep = ""))
}