#Download RTCGAToolbox
source("https://bioconductor.org/biocLite.R") 
biocLite("RTCGAToolbox")

# Download the data and copy it to the ¡°Data¡± variable
Data = getFirehoseData (dataset="COAD",runDate="20160128",clinical = TRUE, RNASeqGene = TRUE, mRNAArray = TRUE, Mutation = TRUE)

# Analysis of differential expressed genes (DEGs) in tumor and normal tissues, draw heatmap and volcanic map.
COAD diffGenes = getDiffExpressedGenes(dataObject=Data,DrawPlots=TRUE,adj.method="BH",adj.pval=0.05,raw.pval=0.05, logFC=2,hmTopUpN=50,hmTopDownN=0)

# Output the result of DEGs into CSV file
toptableOut = showResults(BRCAdiffGenes[[1]])
write.csv(toptableOut,"toptableOut1.csv")

#Survival analysis
clinicData = getData(Data, "clinical")          
write.csv(clinicData,file="clinicData.csv")    
clinicData = clinicData[, 3:5] 
clinicData[is.na(clinicData[, 3]), 3] = clinicData[is.na(clinicData[, 3]), 2]
survData = data.frame(Samples=rownames(clinicData), Time=as.numeric(clinicData[, 3]), Censor=as.numeric(clinicData[, 1])) 
getSurvival(dataObject=Data, geneSymbols=c("MYC"), sampleTimeCensor=survData)

#MYC expression between tumor and normal tissues
for (j in 1:length(Data@mRNAArray)) {
  tmpObj <- Data@mRNAArray[[j]]  
  geneMat <- tmpObj@DataMatrix  
  sampleIDs = colnames(geneMat)  
  samplesDat <- data.frame(matrix(nrow = length(sampleIDs), ncol = 7))  
  rownames(samplesDat) <- sampleIDs  
  for (j in 1:length(sampleIDs)) {  
    if (grepl("\\.", sampleIDs[j])) {   
      tmpRow <- unlist(strsplit(sampleIDs[j], split = "\\."))    
      samplesDat[sampleIDs[j], ] <- tmpRow    } 
    else {  tmpRow <- unlist(strsplit(sampleIDs[j], split = "-"))      
    samplesDat[sampleIDs[j], ] <- tmpRow    }  }  
  sampleIDs1 <- as.character(samplesDat[, 4]) 
  sampleIDs1 <- substr(sampleIDs1, 1, nchar(sampleIDs1) -  1) 
  sampleIDs1 <- as.numeric(sampleIDs1) 
  normalSamples <- rownames(samplesDat)[sampleIDs1 < 20 & sampleIDs1 > 9] 
  tumorSamples <- rownames(samplesDat)[sampleIDs1 <10]}
MYCnormal=Data@mRNAArray[[1]]@DataMatrix["MYC",normalSamples]
MYCtumor=Data@mRNAArray[[1]]@DataMatrix["MYC",tumorSamples]
boxplot(MYCnormal,PIK3CAtumor,col = c("blue", "red"),ylab="mRNAArray", main="MYC", names=c("normal","tumor"))