引言

    上一期内容我们介绍了基于R语言使用热图（Heatmap）对微生物丰度进行展示，今天这期内容主要介绍如何使用弦图（Chord Diagram）来展示物种丰度的计算结果！

正文——代码

1、工作目录设置及R包的加载

rm(list=ls())
setwd("D:\\桌面\\SCI论文写作与绘图物种丰度计算及可视化")
#安装、加载包
install.packages("circlize")
install.packages("statnet")
library(circlize)
library(statnet)

2、加载数据并对其进行处理

#准备数据（此前计算丰度生成的数据）
data <- read.table("Genus_x.txt",sep="\t",header = T,row.names = 1,check.names = F)
data <- as.matrix(m)#转换数据格式
#生成作图数据
df <- data.frame(from = rep(rownames(data), ncol(data)),
                 to = rep(colnames(data), each = nrow(data)),
                 value = as.vector(data))

image.png

image.png

3、绘图

1) 颜色设定

color=NULL
color[c("A","B","C","D","E")]=c("blue","red","yellow","green","pink")
color[rownames(data)]=c("#40A4D8","#33BEB7","#B2C224","#FECC2F","#FBA127",
                           "#F66320","#DB3937","#A463D7","#0C5BCE","grey","black")

2) 绘图

chordDiagram(df, 
             grid.col =color,#颜色
             annotationTrack = "grid",
             transparency = 0.2,#透明度
             link.lwd = 0.00001,#线条宽度
             link.lty = 1,    # 线路类型
             link.border = 0,#边框颜色
             directional = -1,#表示线条的方向，0代表没有方向，1代表正向，-1代表反向，2代表双向
             diffHeight = mm_h(3),#外圈和中间连线的间隔
             direction.type = c("diffHeight","arrows"), #线条是否带有箭头
             link.arr.type = "big.arrow",#箭头类型
             annotationTrackHeight = c(0.04, 0.1))#网格高度

image.png

3) 添加标签并设置标签方向

circos.track(track.index = 1, panel.fun = function(x, y) {
  circos.text(CELL_META$xcenter, CELL_META$ylim[1], CELL_META$sector.index,
              facing = "clockwise", niceFacing = T, adj = c(-0.5, 0.5), cex = 0.8)
  circos.axis(h = "top", labels.cex = 0.4,labels.niceFacing = F, labels.pos.adjust =F)
}, bg.border = NA)

image.png

4）生成图例

legend("right",pch=20,legend=rownames(data),
       col=color[rownames(data)],bty="n",
       cex=1,pt.cex=3,border="black")

image.png

4、保存

pdf(file="1.pdf", width=9, height=5, pointsize=8)
chordDiagram(df, 
             grid.col =color,
             annotationTrack = "grid",#diy添加label和axis
             transparency = 0.2,#透明度
             link.lwd = 0.00001,#线条宽度
             link.lty = 1,    # 线路类型
             link.border = 0,#边框颜色
             directional = -1,#表示线条的方向，0代表没有方向，1代表正向，-1代表反向，2代表双向
             diffHeight = mm_h(3),#外圈和中间连线的间隔
             direction.type = c("diffHeight","arrows"), #线条是否带有箭头
             link.arr.type = "big.arrow",#箭头类型
             annotationTrackHeight = c(0.04, 0.1))#网格高度
circos.track(track.index = 1, panel.fun = function(x, y) {
  circos.text(CELL_META$xcenter, CELL_META$ylim[1], CELL_META$sector.index,
              facing = "clockwise", niceFacing = T, adj = c(-0.5, 0.5), cex = 0.8)
  circos.axis(h = "top", labels.cex = 0.4,labels.niceFacing = F, labels.pos.adjust =F)
}, bg.border = NA)
legend("right",pch=20,legend=rownames(data),
       col=color[rownames(data)],bty="n",
       cex=1,pt.cex=3,border="black") # 设定图例
dev.off()

image.png

此时图例已经和图形主体部分分开，但是图中标签还是比较混乱，需要我们使用进行美化。

5、AI美化

image.png

源码及数据在公众号后台回复获取！！！