经常会想到用热图来展示某个基因或某些基因的表达量问题，今天用R中pheatmap包一步步绘制热图。
第一步：公众路径设置，调用包pheatmap,读取目的文件，查看文件。
1 rm(list=ls()) 2 setwd("D:/VIP/ARSTUDYLOCATION/heatmap/heatmap/") 3 getwd() 4 5 library(pheatmap) 6 library(ggplot2) 7 8 data <- read.table("test.FPKM.txt",header=T,row.names=1,sep="\t") 9 dim(data) 10 head(data)
第二步：逐步深入绘制热图（图1-图15）
一建热图（图1） p<-pheatmap(data) 设置标准化方向scale，对其横向标准化 p<-pheatmap(data,scale="row") 设置边框为白色，横向纵向聚类为无；border="white;cluster_cols = F;cluster_rows = F p<-pheatmap(data,scale="row",border="white",cluster_cols = F,cluster_rows = F)
图1
去掉横纵坐标中的id；show_rownames = F,show_colnames = F（图2） p<-pheatmap(data,scale="row",show_rownames = F,show_colnames = F,border="white",cluster_cols = F,cluster_rows = F)
图2 去掉横轴和纵轴的名称
去掉右上角图例;legend = F（图3） p<-pheatmap(data,scale="row",show_rownames = F,show_colnames = F,legend = F,border="white",cluster_cols = F,cluster_rows = F)
图3 将右上角的图例去掉
设置右上角图例的范围；legend_breaks=c(-1,1)（图4） p<-pheatmap(data,scale="row",legend_breaks=c(-1,0,1),show_rownames = F,show_colnames = F,legend = T,border="white",cluster_cols = F,cluster_rows = F) p<-pheatmap(data,scale="row",legend_breaks=c(-2,0,2),show_rownames = F,show_colnames = F,legend = T,border="white",cluster_cols = F,cluster_rows = F)
图4 更改图例范围
设置图中字的大小；fondsize（图5） #图表字体：命令：fondsize=2/8 p<-pheatmap(data,scale="row",fontsize = 2,show_rownames = T,show_colnames = T,legend = F,border="white",cluster_cols = F,cluster_rows = F) p2<-pheatmap(data,scale="row",fontsize = 8,show_rownames = T,show_colnames = T,legend = F,border="white",cluster_cols = F,cluster_rows = F)
图5 设置字的大小
改变横向和纵向字体大小；fontsize_row = 8,fontsize_col=12 (图6) p<-pheatmap(data,scale="row",fontsize_row = 8,fontsize_col = 12,show_rownames = T,show_colnames = T,legend=T,border="white",cluster_cols = T,cluster_rows = T) p<-pheatmap(data,scale="row",fontsize_row = 12,fontsize_col = 8,show_rownames = T,show_colnames = T,legend=T,border="white",cluster_cols = T,cluster_rows = T)
图6 改变横向和纵向字体的大小
设置横向纵向的树高；treeheight_col = 20,treeheight_row = 15（图7） p<-pheatmap(data,scale="row",border="white",cluster_cols = T,treeheight_col = 20,cluster_rows = T,treeheight_row = 15) p<-pheatmap(data,scale="row",border="white",cluster_cols = T,treeheight_col = 20,cluster_rows = T,treeheight_row = 20)
图7 设置横向和纵向聚类热图的树形高度
原文：https://www.cnblogs.com/smyang/p/12833694.html