corrplot包绘制相关性图

corrplot是一个绘制相关矩阵和置信区间的包，它也包含了一些矩阵排序的算法。

在Rstudio中，直接安装如下：

安装好直接进行下面代码输入：

library(corrplot)

a<-read.delim("R.txt",row.names=1,sep="\t", header=T) #读取R.txt数据，为测序或者芯片数据

b<-cor(a)

corrplot(b)

#还可以用饼图（pie），颜色（color）等等来显示

corrplot(b,method="ellipse",order = "hclust",addrect = 3)

corrplot.mixed(b,lower = "ellipse", upper = "circle")

corrplot(b,method="color",addCoef.col="grey") #用颜色显示

col1=colorRampPalette(c("navy", "white", "firebrick3")) #设置颜色，正相关为红色，负相关为海军蓝色

col2=colorRampPalette(c("#7F0000", "red", "#FF7F00", "yellow", "white","cyan", "#007FFF", "blue", "#00007F"))#设置颜色

col3=colorRampPalette(c("#67001F","#B2182B","#D6604D","#F4A582","#FDDBC7","#FFFFFF","#D1E5F0","#92C5DE","#4393C3", "#2166AC", "#053061"))#设置颜色

col4 = colorRampPalette(c("red", "white", "blue")) #设置颜色

col5=colorRampPalette(c("#7F0000","red","#FF7F00","yellow","#7FFF7F","cyan", "#007FFF", "blue", "#00007F"))#设置颜色

whiteblack <- c("white", "black")#设置颜色

以上为不同颜色命令设置，下面可以自动选择想要的颜色。

1】corrplot(b, method = "ellipse")

3】corrplot.mixed(b)

4】corrplot(b, type = "upper", order = "hclust",col = col1(200),cl.length = 21)

5】corrplot(b, p.mat =res1$p, insig = "p-value", sig.level = -1)

6】res1 <- cor.mtest(mtcars, conf.level = .95)

corrplot(b, p.mat = res1$p, insig = "label_sig",sig.level = c(.001, .01, .05), pch.cex = .9, pch.col = "white")

7】p.mat <- cor.mtest(b)$p

corrplot(b, p.mat =p.mat, method = "color", type = "upper",sig.level = c(.001, .01, .05), pch.cex = .9,insig = "label_sig", pch.col = "white", order = "AOE")

8】p.mat <- cor.mtest(b)$p

corrplot(b, p.mat =p.mat, insig = "label_sig", pch.col = "white",pch = "p<.05", pch.cex = .5, order = "AOE")

9】p.mat <- cor.mtest(b)$p

corrplot(b, method = "color", col = col1(200),cl.length = 21,type = "upper", order = "AOE", number.cex = .7,addCoef.col = "black",tl.col = "black", tl.srt = 90,p.mat = p.mat, sig.level = 0.01, insig = "blank",diag = FALSE)