Missing ratio: 19.01826%
Jump to navigation
Jump to search
RawNARemove<-function(data,missratio=0.3){ threshold<-(missratio)*ncol(data) NaRaw<-which(apply(data,1,function(x) sum(is.na(x))>=threshold)) zero<-which(apply(data,1,function(x) all(x==0))==T) NaRAW<-c(NaRaw,zero) if(length(NaRAW)>0){ data1<-data[-NaRAW,] }else{ data1<-data; } data1 } setwd("/oasis/tscc/scratch/shg047/Estellar2016/mergeHapinfo") data<-read.table("Estellar2016.MHL.txt",head=T,row.names=1) dim(data) data=RawNARemove(data) library("impute") data<-impute.knn(data.matrix(data))$data sum(is.na(data))/(nrow(data)*ncol(data)) newdata<-t(na.omit(data)) mydata <- scale(newdata) # standardize variables d <- dist(mydata, method = "euclidean") # distance matrix fit <- hclust(d, method="ward") pdf("hclust.pdf") plot(fit) # display dendogram dev.off() x1<-grep("tumor|adenocarcinoma",colnames(data)) data1<-data[,x1] save(data1,file="Estellar2016.tumor.MHL.RData") x2<-grep("normal",colnames(data)) data2<-data[,x2] save(data2,file="Estellar2016.normal.MHL.RData")