R/FliudGMPredict.R

In bvnlab/SCATTome: FluidgmR

FliudGMPredict <-
function(TrainGene=NULL, test, ColumnThreshold, RowThreshold, GeneNumbers, readfile=0){

source("Fluidigm.r");

if(readfile==1){

GeneListObject=read.table("GeneListObject.txt", header=FALSE, sep=" ", as.is=TRUE);
TrainData=read.csv("TrainDataMod.csv", header=TRUE, as.is=TRUE, fill=TRUE);
Center=read.csv("TrainMeanSD.csv",  header=TRUE, as.is=TRUE, fill=TRUE);
CenterMean=Center[,1];
CenterSD=Center[,2];
ImportantGeneList=read.csv("RandomForestgeneList.csv", header=TRUE, as.is=TRUE, fill=TRUE);
LassoGenes=read.csv("LASSOgeneList.csv", header=TRUE, as.is=TRUE, fill=TRUE);

TrainGene=list(Index=GeneListObject[[1]], TrainData=TrainData, CenterMean=CenterMean, CenterSD=CenterSD, ImportantGeneList=ImportantGeneList[,1], LassoGenes=LassoGenes[,1])

}

#Training Data 

if(!(TrainGene$Index=="GeneListObject")){

print("GeneListObject Not Detected. Exit NULL");
return(NULL);

}
#Test Data

dtest<-read.csv(test, as.is=TRUE, fill=TRUE, header=TRUE);
ct<-checkData(dtest, Type="Test");

if(ct==1){
b3<-ExcludeData(dtest, ColumnThreshold=ColumnThreshold, RowThreshold=RowThreshold, Type="Test");
}
TestCells<-b3$Data[,1];
b4<-MultImpute(b3$Data, Type="Test");
b5<-MultImpute(b4, Type="Test");
b5<-na.omit(b5)

b6<-ScaleCenterTest(b5, TrainGene$CenterMean, TrainGene$CenterSD);

GeneImp<-c();

for(i in 1:length(TrainGene$ImportantGeneList)){

if(length(which(TrainGene$LassoGenes==TrainGene$ImportantGeneList[i]))>0)GeneImp<-c(GeneImp,TrainGene$ImportantGeneList[i]);

}

b6[,1]<-TestCells;


Final<-PredictEnsemble(train=TrainGene$TrainData, test=b6, GeneImp, GeneNumbers)

testID<-colnames(test);
inclID<-colnames(b3);
exclID<-c();

for(i in 1:length(testID)){

if(length(which(inclID==testID[i]))==0)exclID<-c(exclID,testID[i]);

}
b6[,1]<-TestCells;

write.csv(TrainGene$TrainData, "TrainDataAfterExclusion.csv", row.names=FALSE, quote=FALSE);
write.csv(b6[,-dim(b6)[2]], "TestDataAfterExclusion.csv", row.names=FALSE, quote=FALSE);

TrainROC(train=TrainGene$TrainData, GeneImp, GeneNumbers)


return(list(ImportantGenes=GeneImp[1:GeneNumbers], ExcludedGene_Test=exclID));

}