R语言-limma差异分析与heatmap绘制

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R语言-limma差异分析与heatmap绘制,第1张

#mRNA表达矩阵与GROUP文件样式,heatmap样式见文章最后

library(limma)

 mRNA <- read.table("表达矩阵.txt",sep = "\t",header = T,comment.char = "!",encoding = "UTF-8")

#mRNA数据框行名为基因名,列命为样本名称

 group <- read.table("GROUP.txt",header=T,sep = "\t",encoding = "UTF-8")

 group_CP <- group$treat 

 m_design<- model.matrix(~0+factor(group_CP))

 colnames(m_design) = levels(factor(group_CP))

 rownames(m_design)= group$ID

 contrast.matrix<-makeContrasts("P-C",levels=m_design) #注意P-C顺序,实验组要在前面否则影响上下调结果

 m_fit <- lmFit(mRNA,m_design)

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

 m_fit <- eBayes(m_fit)

 m_genlist <- topTable(m_fit, coef = 1, n=Inf)  #limma结果

#将表达矩阵与差异分析结果合并

  ID_REF <- rownames(m_genlist)

  m_genlist <- data.frame(ID_REF,m_genlist)

  ID_REF <- rownames(mRNA)

  mRNA <- data.frame(ID_REF,mRNA)

  test <-merge(mRNA,m_genlist,by = "ID_REF")

  result <- subset(test,P.Value<0.05)

  row.names(result) <- result[,1]

#绘制热图

heatmap <- result[2:(nrow(group)+1)]

annotation <- data.frame(Factor = factor(group$treat)) #标注样本的分组信息

rownames(annotation) <- colnames(heatmap)

library(pheatmap)

filename <- paste("文件名",".pdf",sep="")

pdf(filename)

pheatmap(heatmap,

        annotation=annotation,

        annotation_legend = TRUE,

        main=filename ,

        scale = "row",

        show_rownames = F,

        color = colorRampPalette(c("green","black","red"))(100))

dev.off()

#表达矩阵与GROUP文件如下所示

您好,这样的:步骤1:打开你电脑中的杀毒软件步骤2:关掉杀毒软件的实时防护/监控功能步骤3:在线或本地安装你要装的R安装包步骤4:安装完R安装包后,重新打开杀毒软件的实时防护/监控功能。步骤5:在R中运行你刚才安装的包。sion 3.0.1 (2013-05-16)Platform: i386-w64-mingw32/i386 (32-bit)locale:[1] LC_COLLATE=Chinese (Simplified)_People's Republic of China.936[2] LC_CTYPE=Chinese (Simplified)_People's Republic of China.936[3] LC_MONETARY=Chinese (Simplified)_People's Republic of China.936[4] LC_NUMERIC=C[5] LC_TIME=Chinese (Simplified)_People's Republic of China.936attached base packages:[1] stats graphics grDevices utils datasets methods base