R package：circlize环状热图

参考文献：https://www./post/r-circlize-study-2/

环状基因表达热图.png

1.读取基因表达数据

这是我的基因表达量数据

Fig1.PNG

myfiles <- list.files(pattern = '*.csv')myfilesmatrix<-read.csv(myfiles[1],sep=',',header=T,check.names = FALSE,row.names = 1)

1.1提取部分数据集

matrix<-subset(matrix,padj<0.2)

1.2提取基因表达值所在的列，组成新的矩阵，并将矩阵转置

为什么要转置，参考https://www.jianshu.com/p/115d07af3029

mat =t(matrix[,7:12])

7-12列为每个样本的基因表达量

1.3基因表达归一化

mat=scale(mat, center = TRUE, scale = TRUE)View(mat)

scale函数可以对矩阵归一化；参考https://www.jianshu.com/p/115d07af3029

1.4对数据进行聚类,从而得到其dendrogram对象

dend <-as.dendrogram(hclust(dist(t(mat))))

dist函数计算microRNA间的距离，hclust来进行层次聚类

1.5定义进化树颜色

library(dendextend)n=3dend <-dend %>% set('branches_k_color', k = n) 

n可自定义

1.6可视化

par(mar=c(7.5,3,1,0))plot(dend)

Fig2.png

1.7聚类后的矩阵

如图Fig 2，聚类后的矩阵的列的顺序会发生变化。按此顺序，重新排列矩阵。

mat2 = mat[, order.dendrogram(dend)]

1.7.1查看矩阵重排后的样本名

lable1=row.names(mat2);lable1[1] 'H-CK-1-3' 'H-CK-2-3' 'H-CK-3-3' 'H-PA-1-3' 'H-PA-2-3' 'H-PA-3-3'

1.7.2查看矩阵重排后的基因名

lable2=colnames(mat2);lable2

只有基因名顺序，也就是列名顺序发生变化。

nr = nrow(mat2);nr[1] 6nc = ncol(mat2);nc[1] 86

1.8 构建颜色转变函数

require('circlize')col_fun = colorRamp2(c(-1.5, 0, 1.5), c('skyblue', 'white', 'red'))

1.9 矩阵中的数值转变为颜色

col_mat = col_fun(mat2)

1.9.1 查看第1列

col_mat[,1]

1.9.1.1 结果

H-CK-1-3 H-CK-2-3 H-CK-3-3 H-PA-1-3 H-PA-2-3 H-PA-3-3 '#FF0000FF' '#FFDED3FF' '#FFAF96FF' '#ABDBF1FF' '#DCF0F9FF' '#BDE3F4FF'

2.1 画板初始化设置

par(mar=c(0,0,0,0))circos.clear();circos.par(canvas.xlim =c(-1.3,1.3),                          canvas.ylim = c(-1.3,1.3),                          cell.padding = c(0,0,0,0),                           gap.degree =90)factors = 'a'circos.initialize(factors, xlim = c(0, ncol(mat2)))

xlim和ylim设置1.3，是为了防止添加基因名时溢出

2.2 添加第一个轨道

circos.track(ylim = c(0, nr),bg.border = NA,track.height = 0.1*nr, panel.fun = function(x, y) { for(i in 1:nr) { circos.rect(xleft = 1:nc - 1, ybottom = rep(nr - i, nc), xright = 1:nc, ytop = rep(nr - i + 1, nc), border = 'white', col = col_mat[i,]) circos.text(x = nc, y = 6.4 -i, labels = lable1[i], facing = 'downward', niceFacing = TRUE, cex = 0.6, adj = c(-0.2, 0)) }})

2.3 添加基因名称

for(i in 1:nc){  circos.text(x = i-0.4,              y = 7,              labels = lable2[i],              facing = 'clockwise', niceFacing = TRUE,              cex = 0.4,adj = c(0, 0))  }

2.4 添加进化树

max_height <-max(attr(dend, 'height'))circos.track(ylim = c(0, max_height),bg.border = NA,track.height = 0.3, panel.fun = function(x, y){ circos.dendrogram(dend = dend, max_height = max_height) })circos.clear()

2.5 添加图例

library(ComplexHeatmap)lgd <- Legend(at = c(-2,-1, 0, 1, 2), col_fun = col_fun,               title_position = 'topcenter',title = 'Z-score')draw(lgd, x = unit(0.7, 'npc'), y = unit(0.7, 'npc'))