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#import data | |
x <- read.table(file="DNAmet.txt",header=T,sep="\t") | |
head(x) | |
# a b c d e | |
#1 PYROXD2 HPSE2 LOXL4 ABCC2 KAZALD1 | |
#2 ENTPD7 ENTPD7 HPSE2 SH3PXD2A BTRC | |
#3 BLOC1S2 SCD ENTPD7 VWA2 FBXW4 | |
#4 FAM178A FGF8 ABCC2 ADARB2 NOLC1 | |
#5 FBXW4 ABLIM1 SCD CHST15 ELOVL3 |
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pc <- c(65,51,29,75,50,1,70,47,37,36,45,44,57,66,60,71,40,39,34,21,27,17,43,19,49,88,58,55,30,18,64,74,72,63,26,22,28,52,35,23,68,41,62,24)#define the columns that you are interested in | |
t1 <- y[obj,pc]#making group1 | |
t2 <- y[obj,-pc]#making group2 | |
t <- cbind(t1,t2) | |
#define the comparison | |
c <- c(rep(1,44),rep(0,52)) |
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#https://www1.doshisha.ac.jp/~mjin/R/36/36.htmlが参考になる。 | |
#ID, OS, Status, DrugからなるTableを作る! | |
#ID= Patient Number,OS =length of time, Status =Death or Not, Drug=Control or test | |
library(survival) | |
#ファイルの読み込み | |
t <- read.table(file="FILE NAME.txt",header=T,sep="t",row.names=1) | |
#分析 |
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#clustering | |
library(pheatmap) | |
x <- read.table("summary_est_mod.txt",header=T,sep="\t") | |
head(x) | |
y <- cor(x[,3:ncol(x)]) | |
pheatmap(y) | |
#making a data file for analusis | |
z <- x[,3:ncol(x)] |
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#making a list of the files in the folder "est" | |
estDataFiles <- list.files("est", pattern = "\\.txt$", full.names=TRUE) | |
estDataFiles | |
#inpu the files | |
listoftables <- lapply(estDataFiles, read.table, header=T, sep="\t") | |
names(listoftables) <- estDataFiles | |
#confirmation | |
head(listoftables[[1]]) |
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#Initially, you need to normalize raw microarray data and make a spread sheet for gene expression as shown elsewhere. | |
#input spread sheet for microarray data | |
x = read.table("XXXX.txt",header=T,sep="\t") | |
x2 = x[,2:ncol(x)] | |
x2 = as.matrix (x2) |