firebrowse下載TCGA數(shù)據(jù)

##用R處理數(shù)據(jù)

dat = read.table("mirna.txt",header=T,sep="\t")

View(head(dat))

dim(dat)

dat1 = dat[-1,c(1,seq(3,ncol(dat)-1,3))]

View(head(dat1))

dat2 = dat1[,-1]

rownames(dat2) = dat1[,1]

View(head(dat2))

library(stringr)

dat.tumor = dat2[,str_detect(colnames(dat2),'.01')]

dim(dat.tumor)

dat.normal = dat2[,str_detect(colnames(dat2),'.11A')]

dim(dat.normal)

dat.final = cbind(dat.tumor,dat.normal)

write.table(dat.final,"datExp.txt",col.names = T,row.names = T,quote=F,sep="\t")

dat.exp = read.table("datExp.txt",header=T,sep="\t")

View(head(dat.exp))

dat.exp[dat.exp == 0] = 1

dat.exp = log(dat.exp,2)

View(dat.exp)

#####-----

pheno = NULL

pheno$sample = colnames(dat.exp)

pheno$group = c(rep('tumor',ncol(dat.tumor)),rep('normal',ncol(dat.normal)))

pheno = as.data.frame(pheno)

head(pheno)

library(limma)

Group = factor(pheno$group,levels=c('tumor','normal'))

design = model.matrix(~0+Group)

colnames(design) <- c('tumor','normal')

design

fit <- lmFit(dat.exp, design)

#構(gòu)建比對模型，比較兩個條件下的表達(dá)數(shù)據(jù)

contrast.matrix <- makeContrasts(tumor-normal,#1

levels=design)

fit2 <- contrasts.fit(fit, contrast.matrix)

#貝葉斯檢驗(yàn)

fit2 <- eBayes(fit2)

#找出差異基因檢驗(yàn)結(jié)果并輸出符合條件的結(jié)果

all.deg = NULL

diff = topTable(fit2,adjust.method="fdr",coef=1,p.value=0.05,

lfc=log(2,2),number=50000,sort.by = 'logFC')

write.table(diff,'DEG.txt',col.names=T,row.names=T,quote=F,sep="\t")

##火山圖

diff0 = diff

P.value = diff0$adj.P.Val

FC = diff0$logFC

df <- data.frame(P.value,FC)

df$threshold = as.factor(abs(df$FC) > log(1.5,2) & df$P.value < 0.05)

levels(df$threshold) = c('grey','red')

df$logp = -log10(df$P.value)

#using base

plot(x = df[,2],y = df[,4], pch=16, col=df$threshold,

xlab="Fold change", ylab="-Log10(Pvalue)",

cex=0.5, main="Volcano Plot")

abline(v=c(-log(1.5,2),log(1.5,2)), h=-log10(0.05),col="green")

#using ggplot2

library(ggplot2)

ggplot(data=df,aes(x=FC,y=-log10(P.value)))+

geom_point(color=df$threshold)