diff --git a/RAutoClDs.R b/RAutoClDs.R
new file mode 100644
index 0000000..f126d6e
--- /dev/null
+++ b/RAutoClDs.R
@@ -0,0 +1,752 @@
+#Efrain H. Gonzalez
+#6/19/2017
+#Libraries required to run the code
+library(pryr)
+library(MASS)
+library(dplyr)
+library(tidyr)
+library(readr)
+library(stringr)
+ 
+
+#Necessary Functions
+#1#Function for handling the changing of row names and column names
+chngrownm <- function(mat){
+	row <- dim(mat)[1]
+	col <- dim(mat)[2]
+	j <- 1
+	x <- 1
+	p <- 1	
+	a <- 1 
+	b <- 1
+	g <- 1
+	for(j in 1:col){
+		if("!Sample_source_name_ch1"==mat[1,j]){
+			colnames(mat)[j] <- "Brain_Region"	
+		} 
+		if("!Sample_title" == mat[1,j]){
+			colnames(mat)[j] <- "Title"
+		} 
+		if("!Sample_geo_accession" == mat[1,j]){
+			colnames(mat)[j] <- "ID_REF"
+		} else{
+			if(grepl("Sex|gender|Gender|sex",mat[2,j])==TRUE){
+				colnames(mat)[j] <- paste0("Sex",x)
+				x = x + 1
+			}
+			if(grepl("postmorteminterval|PMI|pmi",mat[2,j])==TRUE){
+				colnames(mat)[j] <- paste0("PMI",p)
+				p = p + 1
+			}
+			if(grepl("age|Age|AGE",mat[2,j])==TRUE){
+				colnames(mat)[j] <- paste0("Age",a)
+				a = a + 1
+			 }
+			if(grepl("braak|b&b",mat[2,j])==TRUE){
+				colnames(mat)[j] <- paste0("Braak",b)
+				b = b + 1
+			}
+			if(grepl("group|disease|control|AD|normal|diagnosis|Alzheimer|Control|Normal",mat[2,j])==TRUE){
+				colnames(mat)[j] <- paste0("Group",g)
+				g = g + 1
+			}
+			
+		}
+		j = j + 1
+	}
+	mat
+}			
+
+#2#Function for reorganizing information within the columns
+cinfo <- function(mat){
+	col <- dim(mat)[2]
+	j <-2
+	for(j in 2:col){
+		if(grepl("Group",colnames(mat)[j]) == TRUE){
+			mat[,j] <- gsub(".+:\\s|\\s.+;.+","",mat[,j])
+		}
+		if(grepl("Age",colnames(mat)[j])==TRUE){
+			mat[,j] <- gsub("\\D","",mat[,j])%>%
+				as.integer()
+		}
+		if(grepl("Sex",colnames(mat)[j])==TRUE){
+			mat[,j] <- gsub(".+:\\s","",mat[,j])
+		}
+		if(grepl("PMI",colnames(mat)[j])==TRUE){
+			mat[,j] <- gsub("[^0-9\\.]","",mat[,j])%>%
+				as.numeric() 
+		}
+		if(grepl("Braak",colnames(mat)[j])==TRUE){
+			mat[,j]<-gsub(".+:\\s","",mat[,j])%>%
+				as.roman()%>%
+				as.integer()
+		}
+	j=j+1
+	}
+	mat
+}
+
+#3#Function for labeling the gene IDs without names
+NAFIXING <- function(GIDNAM){
+	row <- dim(GIDNAM)[1]
+	i <- 1
+	for(i in 1:row){
+		if(grepl("^NA\\s*$",GIDNAM[i,2])==TRUE||is.na(GIDNAM[i,2])==TRUE){
+			GIDNAM[i,2] <- GIDNAM[i,1]
+		}
+		i <- i + 1
+	}
+	GIDNAM
+}	
+
+#4#Function for changing the gene ID to gene name
+cgeneID <- function(GeneName,DATA){
+    colGene <- dim(GeneName)[2]
+     j <- 1
+     for(j in 1:colGene){
+	chngsreq <- grep(paste0("^",GeneName[1,j],"$"),DATA[1,])
+	if(is.na(sum(chngsreq))==FALSE){
+		if(sum(chngsreq) > 0){
+			DATA[1,chngsreq] <- gsub(paste0("^",GeneName[1,j]),GeneName[2,j],DATA[1,chngsreq])
+		}
+	}
+	j = j+1
+	}
+	DATA
+}
+
+#5#Function for adjusting the gene names
+gcnames <- function(DiData,usecol=1){
+	nuruns <- dim(DiData)[2]
+	i = 1
+	nwnam <- rep("0",length.out=nuruns)
+	for(i in 1:nuruns){
+		if(length(strsplit(colnames(DiData)[i],"///")[[1]]) >= usecol){
+			nwnam[i]=str_trim(strsplit(colnames(DiData)[i],"///")[[1]][usecol])
+		} else{
+			nwnam[i]=str_trim(strsplit(colnames(DiData)[i],"///")[[1]][1])
+		}
+		
+	}
+	nwnam
+
+}
+
+#6# Function for discretizing the data 
+dndat <- function(NDATA){
+	rownd <- dim(NDATA)[1]
+	colnd <- dim(NDATA)[2]
+	DDATA <- matrix(0,nrow=rownd,ncol=colnd)
+	colnames(DDATA) <- colnames(NDATA)
+	i <- 1
+	for(i in 1:rownd){
+		j <- 1
+		for(j in 1:colnd){
+			if(is.na(NDATA[i,j])==FALSE){
+			
+				if(NDATA[i,j] < -1){
+					DDATA[i,j]=0L
+				}
+				if(NDATA[i,j] > 1){
+					DDATA[i,j]=2L
+				}
+				if(-1 <= NDATA[i,j] && NDATA[i,j] < 1){
+					DDATA[i,j]=1L
+				}
+			} else{
+				DDATA[i,j] = NDATA[i,j]
+			}
+			j = j + 1			
+		}
+		i = i + 1
+	}
+	DDATA
+}
+
+
+#MajorFunction#This is the function that does everything else
+THEFT <- function(){
+	#Set working directory based on the directory of the series matrix file Currently only works for windows
+	wd <- getwd()
+	#list.files()
+	#gsub("wd",wd,"Do you want to clean all data files in the directory wd?")
+	numDAT <- switch(EXPR = menu(choices = c("Yes","No"),title = gsub("wd",wd,"Do you want to clean all data files in the directory wd?")) + 1,cat("Nothing done\n"),1L,2L)
+	GSEfileloc <- grep("^GSE.+\\.txt\\.gz$",list.files())
+	
+	#ALL DATA FILES WILL BE CLEANED
+	if(numDAT == 1){
+		#indexing the data files
+		n <- 1	
+		for(n in 1: length(GSEfileloc)){
+			alz <- list.files()[GSEfileloc[n]]
+			
+			#Working with the wordy part of the document
+			alzword <- alz %>%
+				read_delim(delim ="\t",comment = "!Series",col_names = FALSE)%>%
+				filter(grepl("!Sample",X1))%>%
+				filter(!grepl("!Sample_contact",X1))
+			
+			#Getting the GPL file
+			genena <- grep("_platform_id",alzword$X1) %>%
+				alzword$X2[.] %>%
+				str_trim(.) %>%
+				paste0("^",.) %>%
+				grep(.,list.files()) %>%
+				list.files()[.]
+			 
+			#Find out if it is a soft GPL file or not
+			soft <- strsplit(genena,"[\\|/]") %>%
+				.[[1]] %>%
+				.[length(.)] %>%
+				grepl("soft",.)
+			
+			##Changing row names and column names:
+			ALZWORD <- t(alzword)
+			rownames(ALZWORD)=NULL
+			colnames(ALZWORD) <- colnames(ALZWORD,do.NULL=FALSE)
+			ALZWORD <- chngrownm(ALZWORD)[-1,]
+			ALZWORD <- ALZWORD%>%
+				as.data.frame()%>%
+				dplyr::select(-starts_with("col"))
+			
+			##Reorganizing information within the columns and final clinical data
+			ALZWORDF <- cinfo(ALZWORD)
+			
+						
+			#Working with Actual Data part of file
+			alzdat <- alz %>% 
+				read_delim(delim="\t",col_names=TRUE,comment = "!",skip=1)
+			ALZDAT <- t(alzdat[,-1])
+			rownames(ALZDAT)=NULL
+			
+			##Is there a clean version of the GPL file available?
+			gplnum <- strsplit(genena,"[\\|/]") %>%
+				.[[1]] %>%
+				.[length(.)] %>%
+				gsub("\\D","",.)
+			clfileex <- sum(grepl(paste0("Clean_GPL",gplnum),list.files()))
+			if(clfileex >= 1){
+			#use the clean version
+			geneIDNam <-  paste0("Clean_GPL",gplnum,".txt") %>%
+				read_delim(delim="\t",col_names = c("ID","Symbol"), comment = "!")
+			
+			} 
+			if(clfileex == 0){
+			##Lets Create a clean version
+			 
+			##Gene ID to Gene Name
+				if(soft == TRUE){
+					#Check to see if there is already a file containing information on soft files
+					fileex <- sum(grepl("GPL_ID_LOC.txt",list.files()))
+					if(fileex == 1){
+						#Check to see if this GPL soft file has been used before
+						IDF <- read_delim("GPL_ID_LOC.txt",delim = "\t",col_names = TRUE) %>%
+							.$GPL_FILE_NUM%>%
+							grepl(gplnum,.) %>%
+							sum()
+						if(IDF == 1){
+							IDLOCAL <- read_delim("GPL_ID_LOC.txt",delim = "\t",col_names = TRUE) %>%
+								.$GPL_FILE_NUM%>%
+								grep(gplnum,.)
+							idlocgpl <- read_delim("GPL_ID_LOC.txt",delim = "\t",col_names = TRUE) %>%
+									.$LOC_ID %>%
+									.[IDLOCAL]
+							geneIDNam <- genena %>%
+								read_delim(delim="\t",col_names = TRUE, comment = "!", skip = idlocgpl) %>%
+								dplyr::select(.,ID,grep("Symbol|^ORF\\s*$|^gene_assignment\\s*$",colnames(.)))
+						}
+						if(IDF == 0){
+							#No information on this particular GPL file
+							idLOCGPL <- genena %>%
+								read_delim(delim="\t",col_names = FALSE, comment = "!", n_max = 1000) %>%
+								t(.) %>%
+								grep("^ID\\s*$",.) %>%
+								-1
+							cbind(as.integer(gplnum),as.integer(idLOCGPL)) %>%
+								cat(file="GPL_ID_LOC.txt",sep = "\t", fill = TRUE, append = TRUE)
+							geneIDNam <- genena %>%
+								read_delim(delim="\t",col_names = TRUE, comment = "!", skip = idLOCGPL) %>%
+								dplyr::select(.,ID,grep("Symbol|^ORF\\s*$|^gene_assignment\\s*$",colnames(.)))
+						}
+					}
+					if(fileex == 0){
+						#We must create a file that we can access for later use
+						idLOCGPL <- genena %>%
+							read_delim(delim="\t",col_names = FALSE, comment = "!", n_max = 1000) %>%
+							t(.) %>%
+							grep("^ID\\s*$",.) %>%
+							-1
+						Firstval <- cbind(as.integer(gplnum),as.integer(idLOCGPL))
+						colnames(Firstval) <- c("GPL_FILE_NUM","LOC_ID")
+						write.table(Firstval,file = "GPL_ID_LOC.txt", sep = "\t",row.names = FALSE, col.names = TRUE)
+						geneIDNam <- genena %>%
+							read_delim(delim="\t",col_names = TRUE, comment = "!", skip = idLOCGPL) %>%
+							dplyr::select(.,ID,grep("Symbol|^ORF\\s*$|^gene_assignment\\s*$",colnames(.)))
+					}
+	 			}
+				if(soft == FALSE){
+					geneIDNam <- genena %>%
+						read_delim(delim="\t",comment = "#")%>%
+						dplyr::select(.,ID,grep("Symbol|^ORF\\s*$|^gene_assignment\\s*$",colnames(.)))
+				}
+				
+				##Labeling the gene IDs without names
+				geneIDNam <- NAFIXING(geneIDNam)	
+				
+				##remove the whitespace
+				geneIDNam <- t(rbind(str_trim(t(geneIDNam)[1,]),str_trim(t(geneIDNam)[2,])))
+				
+				##Here is the clean version
+				write.table(geneIDNam,file = paste0("Clean_GPL",gplnum,".txt"),sep = "\t",row.names = FALSE, col.names = FALSE)
+			}
+			
+			
+			
+			##Changing the gene ID to gene name
+			ALZDAT1 <- cgeneID(t(geneIDNam),t(alzdat))
+			colnames(ALZDAT) = ALZDAT1[1,]
+						
+			
+			##Adjusting the column names aka the gene names
+			colnames(ALZDAT) <- gcnames(ALZDAT)
+			
+			
+			#Full RAW Data
+			Fullalzdwr <- ALZDAT %>%
+				as.data.frame() %>%
+				cbind(ALZWORDF,.)
+				
+			#Raw file is output
+			nfnaex <- strsplit(alz,"[\\]") %>%
+				.[[1]] %>%
+				.[length(.)] %>%
+				gsub("\\D","",.) %>%
+				c("GSE",.,"aftexcel.txt") %>%
+				paste(collapse = "")
+			write.table(t(Fullalzdwr), file = nfnaex, sep = "\t")
+			
+						
+						
+			#Now for the discretization part
+			##get the wordy part again
+			rawword <- t(ALZWORDF)
+			
+			##where is ID_REF located
+			hereim <- grep("ID_REF",rownames(rawword))
+			
+			##Subject Names GSM...
+			subjnam <- rawword[hereim,]
+			
+			##Getting the names for the rows
+			namedarows <- rownames(rawword)[-hereim] %>%
+				as.data.frame()
+			RAWWORD <- rawword[-hereim,] %>%
+				as.data.frame() %>%
+				bind_cols(namedarows,.)
+			z <- 1
+			naroww <- as.data.frame(rep(0,dim(RAWWORD)[1]),stringsAsFactors = FALSE)
+			for(z in 1:dim(RAWWORD)[1]){
+				naroww[z,1] <- as.integer(sum(is.na(RAWWORD[z,])))
+				z <- z + 1
+			}
+			
+			colnames(naroww) <- "ROW_NAs"
+			RAWWORD <- bind_cols(RAWWORD,naroww)
+			
+			
+			roALZna <- t(ALZDAT) %>%
+				rownames(.) %>%
+				as.data.frame(.)
+			colnames(roALZna) <- "ID_REF"
+			
+			RAWDAT <- t(ALZDAT) %>%
+				as.data.frame(.)
+			colnames(RAWDAT) <- NULL
+			rownames(RAWDAT) <- NULL
+			
+			RAWDAT2 <- RAWDAT %>%
+				cbind(roALZna,.) %>%
+				dplyr::arrange(.,ID_REF)
+			
+			##Editing the file for R processing
+			RAWDATID <- RAWDAT2[,1] %>%
+				as.matrix(.)
+			
+			RAWDATNUM <- RAWDAT2[,-1] %>%
+				mapply(.,FUN = as.numeric) %>%
+				t(.)
+			
+			##Consolidating genes with the same name
+			###create empty matrix of size equal  to tabRDATID
+			tabRDATID <- table(RAWDATID)
+			NuRDATN <- matrix(0, nrow = dim(RAWDATNUM)[1], ncol = length(tabRDATID))
+			j <- 1
+			for(j in 1:length(tabRDATID)){
+				##Putting the ones without duplicates in their new homes
+				if(tabRDATID[j] == 1){
+					NuRDATN[,j] <- RAWDATNUM[,which(RAWDATID==rownames(tabRDATID)[j])]
+				}
+				##Averaging duplicates and putting them in their new homes
+				if(tabRDATID[j] > 1){
+					NuRDATN[,j] <- rowMeans(RAWDATNUM[,which(RAWDATID==rownames(tabRDATID)[j])],na.rm = TRUE)
+				}
+				j <- j + 1
+			}
+			
+			##Scaling the Data
+			scrawdat <- NuRDATN%>%
+				scale()
+			attr(scrawdat,"scaled:center") <- NULL
+			attr(scrawdat,"scaled:scale") <- NULL
+			colnames(scrawdat) <- rownames(tabRDATID)
+			
+			##Discretized the Data
+			dialzdat <- scrawdat %>%
+				dndat(.) %>%
+				t()%>%
+				as.data.frame(.)
+			colnames(dialzdat) <- rownames(RAWDATNUM)
+						
+			##setting "ID_REF" as a new variable
+			geneNAM <- as.data.frame(as.matrix(rownames(dialzdat),ncol=1))
+			colnames(geneNAM) <- "ID_REF"
+			rownames(dialzdat) <- NULL
+			dialzdat <-bind_cols(geneNAM,dialzdat)
+			
+			##NAs in a column
+			x <- 2
+			nacol <- as.data.frame(t(rep(0,dim(dialzdat)[2])),stringsAsFactors = FALSE)
+			nacol[1,1] = "COL_NAs"
+			for(x in 2:dim(dialzdat)[2]){
+				nacol[1,x] <- as.integer(sum(is.na(dialzdat[,x])))
+				x <- x + 1
+			}
+			colnames(nacol) <- colnames(dialzdat)
+			dialzdat <- bind_rows(dialzdat,nacol)
+			
+			##NAs in a row
+			y <- 1
+			narowd <- as.data.frame(rep(0,dim(dialzdat)[1]),stringsAsFactors = FALSE)
+			for(y in 1:dim(dialzdat)[1]){
+				narowd[y,1] <- as.integer(sum(is.na(dialzdat[y,])))
+				y <- y + 1
+			}
+			colnames(narowd) <- "ROW_NAs"
+			dialzdat <- bind_cols(dialzdat,narowd)
+			colnames(dialzdat)[2:(dim(dialzdat)[2]-1)] <- subjnam
+			colnames(RAWWORD) <- colnames(dialzdat)
+			##converting to character so that the clinical can be brought together with discrete data
+			k <- 2
+			for(k in 2:dim(dialzdat)[2]-1){
+				dialzdat[,k] <- as.character(dialzdat[,k])
+				k <- k + 1
+			}
+			#The End the full data
+			Dscrtalzdw <- bind_rows(RAWWORD,dialzdat)
+			
+			#Produces Discrete file
+			nfnaex2 <- strsplit(alz,"[\\|/]") %>%
+				.[[1]] %>%
+				.[length(.)] %>%
+				gsub("\\D","",.) %>%
+				c("GSE",.,"dscrt.txt") %>%
+				paste(collapse = "")
+			write.table(Dscrtalzdw, file = nfnaex2, sep = "\t",col.names = TRUE,row.names = FALSE)
+			n <- n +1
+		}
+	}
+	
+	#CHOOSE A DATA FILE TO CLEAN OR SEVERAL DATA FILES TO CLEAN
+	if(numDAT == 2){
+		#All the files you want to analyze
+		ANDIS <- select.list(choices = list.files()[GSEfileloc],multiple = TRUE, title = "Choose the file/files you want to analyze:")
+		if(length(ANDIS) == 0){
+			#Spit out a warning
+			warning("You did not select any files and so no cleaning will be performed")
+		} else{
+			#indexing the data files
+			n <- 1
+			for(n in 1: length(ANDIS)){
+				alz <- ANDIS[n]
+				
+				#Working with the wordy part of the document
+				alzword <- alz %>%
+					read_delim(delim ="\t",comment = "!Series",col_names = FALSE)%>%
+					filter(grepl("!Sample",X1))%>%
+					filter(!grepl("!Sample_contact",X1))
+				
+				#Getting the GPL file
+				genena <- grep("_platform_id",alzword$X1) %>%
+					alzword$X2[.] %>%
+					str_trim(.) %>%
+					paste0("^",.) %>%
+					grep(.,list.files()) %>%
+					list.files()[.]
+				 
+				#Find out if it is a soft GPL file or not
+				soft <- strsplit(genena,"[\\|/]") %>%
+					.[[1]] %>%
+					.[length(.)] %>%
+					grepl("soft",.)
+				
+				##Changing row names and column names:
+				ALZWORD <- t(alzword)
+				rownames(ALZWORD)=NULL
+				colnames(ALZWORD) <- colnames(ALZWORD,do.NULL=FALSE)
+				ALZWORD <- chngrownm(ALZWORD)[-1,]
+				ALZWORD <- ALZWORD%>%
+					as.data.frame()%>%
+					dplyr::select(-starts_with("col"))
+				
+				##Reorganizing information within the columns and final clinical data
+				ALZWORDF <- cinfo(ALZWORD)
+				
+							
+				#Working with Actual Data part of file
+				alzdat <- alz %>% 
+					read_delim(delim="\t",col_names=TRUE,comment = "!",skip=1)
+				ALZDAT <- t(alzdat[,-1])
+				rownames(ALZDAT)=NULL
+				
+				##Is there a clean version of the GPL file available?
+				gplnum <- strsplit(genena,"[\\|/]") %>%
+					.[[1]] %>%
+					.[length(.)] %>%
+					gsub("\\D","",.)
+				clfileex <- sum(grepl(paste0("Clean_GPL",gplnum),list.files()))
+				if(clfileex >= 1){
+				#use the clean version
+				geneIDNam <-  paste0("Clean_GPL",gplnum,".txt") %>%
+					read_delim(delim="\t",col_names = c("ID","Symbol"), comment = "!")
+				
+				} 
+				if(clfileex == 0){
+				##Lets Create a clean version
+				 
+				##Gene ID to Gene Name
+					if(soft == TRUE){
+						#Check to see if there is already a file containing information on soft files
+						fileex <- sum(grepl("GPL_ID_LOC.txt",list.files()))
+						if(fileex == 1){
+							#Check to see if this GPL soft file has been used before
+							IDF <- read_delim("GPL_ID_LOC.txt",delim = "\t",col_names = TRUE) %>%
+								.$GPL_FILE_NUM%>%
+								grepl(gplnum,.) %>%
+								sum()
+							if(IDF == 1){
+								IDLOCAL <- read_delim("GPL_ID_LOC.txt",delim = "\t",col_names = TRUE) %>%
+									.$GPL_FILE_NUM%>%
+									grep(gplnum,.)
+								idlocgpl <- read_delim("GPL_ID_LOC.txt",delim = "\t",col_names = TRUE) %>%
+										.$LOC_ID %>%
+										.[IDLOCAL]
+								geneIDNam <- genena %>%
+									read_delim(delim="\t",col_names = TRUE, comment = "!", skip = idlocgpl) %>%
+									dplyr::select(.,ID,grep("Symbol|^ORF\\s*$|^gene_assignment\\s*$",colnames(.)))
+							}
+							if(IDF == 0){
+								#No information on this particular GPL file
+								idLOCGPL <- genena %>%
+									read_delim(delim="\t",col_names = FALSE, comment = "!", n_max = 1000) %>%
+									t(.) %>%
+									grep("^ID\\s*$",.) %>%
+									-1
+								cbind(as.integer(gplnum),as.integer(idLOCGPL)) %>%
+									cat(file="GPL_ID_LOC.txt",sep = "\t", fill = TRUE, append = TRUE)
+								geneIDNam <- genena %>%
+									read_delim(delim="\t",col_names = TRUE, comment = "!", skip = idLOCGPL) %>%
+									dplyr::select(.,ID,grep("Symbol|^ORF\\s*$|^gene_assignment\\s*$",colnames(.)))
+							}
+						}
+						if(fileex == 0){
+							#We must create a file that we can access for later use
+							idLOCGPL <- genena %>%
+								read_delim(delim="\t",col_names = FALSE, comment = "!", n_max = 1000) %>%
+								t(.) %>%
+								grep("^ID\\s*$",.) %>%
+								-1
+							Firstval <- cbind(as.integer(gplnum),as.integer(idLOCGPL))
+							colnames(Firstval) <- c("GPL_FILE_NUM","LOC_ID")
+							write.table(Firstval,file = "GPL_ID_LOC.txt", sep = "\t",row.names = FALSE, col.names = TRUE)
+							geneIDNam <- genena %>%
+								read_delim(delim="\t",col_names = TRUE, comment = "!", skip = idLOCGPL) %>%
+								dplyr::select(.,ID,grep("Symbol|^ORF\\s*$|^gene_assignment\\s*$",colnames(.)))
+						}
+		 			}
+					if(soft == FALSE){
+						geneIDNam <- genena %>%
+							read_delim(delim="\t",comment = "#")%>%
+							dplyr::select(.,ID,grep("Symbol|^ORF\\s*$|^gene_assignment\\s*$",colnames(.)))
+					}
+					
+					##Labeling the gene IDs without names
+						geneIDNam <- NAFIXING(geneIDNam)	
+					
+					##remove the whitespace
+					geneIDNam <- t(rbind(str_trim(t(geneIDNam)[1,]),str_trim(t(geneIDNam)[2,])))
+					
+					##Here is the clean version
+					write.table(geneIDNam,file = paste0("Clean_GPL",gplnum,".txt"),sep = "\t",row.names = FALSE, col.names = FALSE)
+				}
+				
+				
+				
+				##Changing the gene ID to gene name
+				ALZDAT1 <- cgeneID(t(geneIDNam),t(alzdat))
+				colnames(ALZDAT) = ALZDAT1[1,]
+							
+				
+				##Adjusting the column names aka the gene names
+				colnames(ALZDAT) <- gcnames(ALZDAT)
+				
+			
+				#Full RAW Data
+				Fullalzdwr <- ALZDAT %>%
+					as.data.frame() %>%
+					cbind(ALZWORDF,.)
+					
+				#Raw file is output
+				nfnaex <- strsplit(alz,"[\\]") %>%
+					.[[1]] %>%
+					.[length(.)] %>%
+					gsub("\\D","",.) %>%
+					c("GSE",.,"aftexcel.txt") %>%
+					paste(collapse = "")
+				write.table(t(Fullalzdwr), file = nfnaex, sep = "\t")
+				
+	 						
+						
+				#Now for the discretization part
+				##get the wordy part again
+				rawword <- t(ALZWORDF)
+				
+				##where is ID_REF located
+				hereim <- grep("ID_REF",rownames(rawword))
+				
+				##Subject Names GSM...
+				subjnam <- rawword[hereim,]
+				
+				##Getting the names for the rows
+				namedarows <- rownames(rawword)[-hereim] %>%
+					as.data.frame()
+				RAWWORD <- rawword[-hereim,] %>%
+					as.data.frame() %>%
+					bind_cols(namedarows,.)
+				z <- 1
+				naroww <- as.data.frame(rep(0,dim(RAWWORD)[1]),stringsAsFactors = FALSE)
+				for(z in 1:dim(RAWWORD)[1]){
+					naroww[z,1] <- as.integer(sum(is.na(RAWWORD[z,])))
+					z <- z + 1
+				}
+				
+				colnames(naroww) <- "ROW_NAs"
+				RAWWORD <- bind_cols(RAWWORD,naroww)
+				
+					
+				roALZna <- t(ALZDAT) %>%
+					rownames(.) %>%
+					as.data.frame(.)
+				colnames(roALZna) <- "ID_REF"
+				
+				RAWDAT <- t(ALZDAT) %>%
+					as.data.frame(.)
+				colnames(RAWDAT) <- NULL
+				rownames(RAWDAT) <- NULL
+				
+				RAWDAT2 <- RAWDAT %>%
+					cbind(roALZna,.) %>%
+					dplyr::arrange(.,ID_REF)
+				
+				##Editing the file for R processing
+				RAWDATID <- RAWDAT2[,1] %>%
+					as.matrix(.)
+				
+				RAWDATNUM <- RAWDAT2[,-1] %>%
+					mapply(.,FUN = as.numeric) %>%
+					t(.)
+				
+				##Consolidating genes with the same name
+				###create empty matrix of size equal  to tabRDATID
+				tabRDATID <- table(RAWDATID)
+				NuRDATN <- matrix(0, nrow = dim(RAWDATNUM)[1], ncol = length(tabRDATID))
+				j <- 1
+				for(j in 1:length(tabRDATID)){
+					##Putting the ones without duplicates in their new homes
+					if(tabRDATID[j] == 1){
+						NuRDATN[,j] <- RAWDATNUM[,which(RAWDATID==rownames(tabRDATID)[j])]
+					}
+					##Averaging duplicates and putting them in their new homes
+					if(tabRDATID[j] > 1){
+						NuRDATN[,j] <- rowMeans(RAWDATNUM[,which(RAWDATID==rownames(tabRDATID)[j])],na.rm = TRUE)
+					}
+					j <- j + 1
+				}
+				
+				##Scaling the Data
+				scrawdat <- NuRDATN%>%
+					scale()
+				attr(scrawdat,"scaled:center") <- NULL
+				attr(scrawdat,"scaled:scale") <- NULL
+				colnames(scrawdat) <- rownames(tabRDATID)
+				
+				##Discretized the Data
+				dialzdat <- scrawdat %>%
+					dndat(.) %>%
+					t()%>%
+					as.data.frame(.)
+				colnames(dialzdat) <- rownames(RAWDATNUM)
+							
+				##setting "ID_REF" as a new variable
+				geneNAM <- as.data.frame(as.matrix(rownames(dialzdat),ncol=1))
+				colnames(geneNAM) <- "ID_REF"
+				rownames(dialzdat) <- NULL
+				dialzdat <-bind_cols(geneNAM,dialzdat)
+				
+				##NAs in a column
+				x <- 2
+				nacol <- as.data.frame(t(rep(0,dim(dialzdat)[2])),stringsAsFactors = FALSE)
+				nacol[1,1] = "COL_NAs"
+				for(x in 2:dim(dialzdat)[2]){
+					nacol[1,x] <- as.integer(sum(is.na(dialzdat[,x])))
+					x <- x + 1
+				}
+				colnames(nacol) <- colnames(dialzdat)
+				dialzdat <- bind_rows(dialzdat,nacol)
+				
+				##NAs in a row
+				y <- 1
+				narowd <- as.data.frame(rep(0,dim(dialzdat)[1]),stringsAsFactors = FALSE)
+				for(y in 1:dim(dialzdat)[1]){
+					narowd[y,1] <- as.integer(sum(is.na(dialzdat[y,])))
+					y <- y + 1
+				}
+				colnames(narowd) <- "ROW_NAs"
+				dialzdat <- bind_cols(dialzdat,narowd)
+				colnames(dialzdat)[2:(dim(dialzdat)[2]-1)] <- subjnam
+				colnames(RAWWORD) <- colnames(dialzdat)
+				##converting to character so that the clinical can be brought together with discrete data
+				k <- 2
+				for(k in 2:dim(dialzdat)[2]-1){
+					dialzdat[,k] <- as.character(dialzdat[,k])
+					k <- k + 1
+				}
+				#The End the full data
+				Dscrtalzdw <- bind_rows(RAWWORD,dialzdat)
+				
+				#Produces Discrete file
+				nfnaex2 <- strsplit(alz,"[\\|/]") %>%
+					.[[1]] %>%
+					.[length(.)] %>%
+					gsub("\\D","",.) %>%
+					c("GSE",.,"dscrt.txt") %>%
+					paste(collapse = "")
+				write.table(Dscrtalzdw, file = nfnaex2, sep = "\t",col.names = TRUE,row.names = FALSE)
+				
+								
+				n <- n + 1
+			}
+		}
+	}
+}
+#The Rest of this code will be used every time you want to change a data set
+THEFT()
\ No newline at end of file