画出美哭了的热图

声明：本帖中代码为小丫画图出品，我只是辛勤的搬运工，侵删。如想学习更多生信知识，请关注下方二维码，打赏后进群，群内干货多多。生信路上自学愉快～（为啥二维码这么大）

微信号：epigenomics

热图必备三要素：配色美美哒，边栏有scale，第三个我编不出来了……

场景一：基因表达量的热图

1 读取数据，加载包

df<-read.table("mRNA.txt",row.names = 1,header = T,as.is = T)
head(df)
library(pheatmap)

2 设置分组，用来画scale

annotation_col = data.frame(
  Gender = factor(rep(c("F","M"),32)),#按性别分组
  type = factor(rep(c("DG","PFC","PCC","CA1","CB","OC","TC","PC"),c(8,8,8,8,8,8,8,8)))) #按样本类别分组
rownames(annotation_col) = colnames(df)

3 设置scale的颜色

ann_colors = list(
  Gender = c(F = "#FFA42D", M = "#A9D9DF"),#给性别分组设置颜色
  type = c(DG = "blue", PFC = "green", PCC = "red", CA1 = "black",
  CB = "pink", OC = "grey", TC = "yellow", PC = "purple")

4 画热图

pheatmap(df[1:1000,], #横行是画基因的相关性
         cellwidth = 8, cellheight = 1, fontsize = 8, #调整格子和字体的大小
         method="spearman", #计算gene或sample之间的相关性的方法，可选"pearson" (default), "kendall", or "spearman"
         scale="row", #为基因做scale
         cluster_rows=T,#为基因做聚类
         cluster_cols=T,#为sample做聚类
         color = colorRampPalette(c("navy", "white", "firebrick3"))(20), #调颜色
         show_colnames=F,show_rownames =F,#图太大了的话横轴和纵轴名就都不显示
         annotation_col = annotation_col, #scale的名字
         annotation_colors = ann_colors,  #scale的颜色
         #treeheight_row = "0",treeheight_col = "0",#不画树
         border_color = "NA")

image.png

场景二：样本相关性的热图

1. 计算样本间的相关性

cormat<-round(cor(df,method = "spearman"),2)

2. 画热图

library(pheatmap)
pheatmap(cormat,cellwidth = 8, cellheight = 8,fontsize = 8,
         color = colorRampPalette(c("#3C7DAF", "#EAF4F1","#FFFCBA", "#E83140"))(20),
         show_colnames=T,show_rownames =T,#显示sample的名字
         #border_color = "NA",#默认有边框，不要边框的话就加这行
         treeheight_row = "0",treeheight_col = "0")#不画树

image.png

3. 显示数字的热图

pheatmap(cormat[4:24,4:24],cellwidth = 15, cellheight = 15,fontsize = 8,
         color = colorRampPalette(c("#3C7DAF", "#EAF4F1","#FFFCBA", "#E83140"))(20),
         show_colnames=T,show_rownames =T,
         display_numbers = TRUE,#显示数字
         treeheight_row = "0",treeheight_col = "0")#不画树

image.png

4. 显示scale 改改配色

#按照sample的顺序，告诉R，它是属于哪个组的
annotation_col = data.frame(
  type = factor(rep(c("DG","PFC","PCC","CA1","CB","OC","TC","PC"),c(8,8,8,8,8,8,8,8))))
rownames(annotation_col) = colnames(df)

annotation_row = data.frame(
  type = factor(rep(c("DG","PFC","PCC","CA1","CB","OC","TC","PC"),c(8,8,8,8,8,8,8,8))))
rownames(annotation_row) = colnames(df)

#然后给每个组设置颜色
ann_colors = list(
  type = c(DG = "blue", PFC = "green", PCC = "red", CA1 = "black",
  CB = "pink", OC = "grey", TC = "yellow", PC = "purple")
)

pheatmap(cormat,cellwidth = 8, cellheight = 8,
         fontsize = 8,
         #display_numbers = TRUE,
         color = colorRampPalette(c("navy", "white", "firebrick3"))(20),
         show_colnames=F,show_rownames =F,#不显示sample的名字
         annotation_col = annotation_col, annotation_row = annotation_row,
         annotation_colors = ann_colors,
         treeheight_row = "0",treeheight_col = "0",#不画树
         border_color = "NA")#不显示边框

image.png

版权原因，数据集不能给出，如想要数据集练习，请扫码进群走大门。小丫画图欢迎你～