其他
基于R语言的微生物群落组成多样性分析——物种丰度可视化之弦图（Chord Diagram）
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！
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)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))绘图
1）颜色设定
color=NULLcolor[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$sector.index, facing = "clockwise", niceFacing = T, adj = c(-0.5, 0.5), cex = 0.8) circos.axis(h = "top", labels.cex = 0.4,labels.niceFacing = F, labels.pos.adjust =F)}, bg.border = NA)4）生成图例
legend("right",pch=20,legend=rownames(data), col=color[rownames(data)],bty="n", cex=1,pt.cex=3,border="black")由于绘图板大小限制，所以此时我们看到生成的图例与标签排版混乱，互相重叠，此时需要我们将其保存成PDF以将图例和图形主体部分分开。
保存
pdf(file="1.pdf", width=9, height=5, pointsize=8)chordDiagram(df, grid.col =color, annotationTrack = "grid",#diy添加label和axis transparency = 0.2,#透明度 link.lwd = 0.00001,#线条宽度 link.lty = 1, # 线路类型 link.border = 0,#边框颜色 directional = -1,#表示线条的方向，0代表没有方向，1代表正向，-1代表反向，2代表双向 diffHeight = mm_h(3),#外圈和中间连线的间隔 direction.type = c("diffHeight","arrows"), #线条是否带有箭头 link.arr.type = "big.arrow",#箭头类型 annotationTrackHeight = c(0.04, 0.1))#网格高度circos.track(track.index = 1, panel.fun = function(x, y) { circos.text(CELL_META$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()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AI进行美化。
AI美化
源码及数据在后台回复“Chord”获取！！！