弦图是一种非常常见的图形，表示互作联系，远的不说，就近期一直说的单细胞互作关系的展示上(iTALK---单细胞受配体互作分析及可视化（详细版教程)，弦图露了很多次面！这里我们举个例子，说说简单的弦图绘制！

首先准备互作数据，设置颜色，有几个项目就设置几种颜色。这里弦图的绘制采用的是circlize包的chordDiagram函数。

setwd("D:/KS项目/公众号文章/环形弦图绘制")

# 读取数据\设置颜色

net <- read.table("df.csv", header = T, sep = ',')

library(circlize)

mycolor <- c("#DC050C", "#FB8072", "#1965B0", "#7BAFDE", "#882E72",

"#B17BA6", "#FF7F00", "#FDB462", "#E7298A", "#E78AC3",

"#33A02C")

绘图。

chordDiagram(

x = net,

grid.col = mycolor,

directional = 1,

direction.type = c("arrows", "diffHeight"),

diffHeight = -0.01,

annotationTrack = c("name", "grid", "axis"),

annotationTrackHeight = c(0.05, 0.08),

link.arr.type = "big.arrow",

link.sort = TRUE,

link.largest.ontop = TRUE,

transparency = 0.25

)

还可以将弦取消，使用箭头连接，更加明了，连接线宽度设置数值，表示互作关系的强弱。

chordDiagram(

x = net,

grid.col = mycolor,

directional = 1,

direction.type = 'arrows',

diffHeight = -0.01,

annotationTrack = c("grid","name"),

annotationTrackHeight = c(0.05, 0.08),

link.arr.type = "triangle",

link.sort = TRUE,

link.largest.ontop = TRUE,

transparency = 0.5,

col='#00000000',#弦的颜色，设置为无

link.arr.lwd=net$value, #连线的宽度

column.col = mycolor

)

最后，我们添加上标题和legend就完成了！

#添加legend

legend("right",

pch=20,

legend=unique(net$SOURCE),

bty="n",

col =mycolor,

cex=1,pt.cex=3,

border="black")

title('Intercellular communication')

这样就完成了

转自：“KS科研分享与服务”微信公众号

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