跟着Nature Communications学作图：R语言ci

论文

A latitudinal gradient of deep-sea invasions for marine fishes

https://www.nature.com/articles/s41467-023-36501-4

s41467-023-36501-4.pdf

论文中对应的图实现的代码都有，链接是

https://github.com/stfriedman/Depth-transitions-paper

里面有个弦图很好看，在论文中对应的是figure3, 对应画图代码是上面链接中的figure2

image.png

论文中的作图数据是没有提供的，这里我就随便构造一个数据，能够把论文中提供的代码运行通就可以

示例数据集

image.png

读取数据集

library(readxl)

dat<-read_excel("data/20230301/20230301.xlsx")
dat

作图代码

circos.clear()
circos.par(start.degree = 90, 
           #gap.degree = 4, 
           points.overflow.warning = FALSE,
           gap.after=c("A1"=5,"A2"=5,"A3"=15,
                       "B1"=5,"B2"=5,"B3"=15,
                       "D1"=5,"D2"=5,"D3"=15))
grid.col<-c("A1"="#B0E0E6","A2"="#2C8EB5","A3"="#16465B",
            "B1"="#B0E0E6","B2"="#2C8EB5","B3"="#16465B",
            "D1"="#B0E0E6","D2"="#2C8EB5","D3"="#16465B")
group<-c("A1"="A","A2"="A","A3"="A",
         "B1"="B","B2"="B","B3"="B",
         "D1"="D","D2"="D","D3"="D")
chordDiagram(dat,
             grid.col = grid.col,
             col = rand_color(nrow(dat)),
             group = group,
             transparency = 0.25,
             directional = 1,
             direction.type = c("arrows", "diffHeight"), 
             diffHeight  = -0.04,
             annotationTrack = "grid", 
             annotationTrackHeight = c(0.08, 0.1),
             link.arr.type = "big.arrow", 
             # link.sort = TRUE, 
             # link.decreasing = TRUE,
             link.largest.ontop = TRUE,
             preAllocateTracks = list(
               track.height = 0.1,
               track.margin = c(0.01, 0)
             ))

circos.trackPlotRegion(
  track.index = 2, 
  bg.border = NA, 
  panel.fun = function(x, y) {
    
    xlim = get.cell.meta.data("xlim")
    #sector.index = get.cell.meta.data("sector.index")
    sector.index = gsub("[a-z]+_", "", get.cell.meta.data("sector.index"))
    
    # Add names to the sector. 
    circos.text(
      x = mean(xlim), 
      y = 0.5, 
      col = "white",
      labels = sector.index, 
      facing = "bending", 
      cex = 1,
      niceFacing = TRUE
    )
  }
)

names(group[7:9])
i<-1
highlight.sector(names(group[7:9]), track.index = 1, facing = "bending", font = 2,
                 col = ifelse(i == 1, "#E6AE48FF", "#E6AE483a"),
                 border = ifelse(i == 1, TRUE, FALSE), 
                 lwd = ifelse(i == 1, 2, 0.01),
                 text = "tropical", cex = 1.5, text.col = "white", niceFacing = TRUE)

highlight.sector(names(group[4:6]), track.index = 1, facing = "bending", font = 2,
                 border = ifelse(i == 2, TRUE, FALSE),
                 lwd = ifelse(i == 2, 2, 0.01),
                 col = ifelse(i == 2, "#20A486", "#20A4863a"),
                 text = "temperate", cex = 1.5, text.col = "white", niceFacing = TRUE)

highlight.sector(names(group[1:3]), track.index = 1, facing = "bending", font = 2,
                 col = ifelse(i == 3, "#472D7B", "#472D7B3a"),
                 border = ifelse(i == 3, TRUE, FALSE),
                 lwd = ifelse(i == 3, 2, 0.01),
                 text = "polar", cex = 1.5, text.col = "white", niceFacing = TRUE)
}

image.png

代码里有很多参数，这里有的我也不太清楚是用来做什么的，先记录实现代码，后续如果有需求做这个图，再来研究具体参数的意思

https://jokergoo.github.io/circlize_book/book/the-chorddiagram-function.html 做这个图可以参考这个链接

image.png

示例数据和代码可以给推文点赞，然后点击在看，最后留言获取

欢迎大家关注我的公众号

小明的数据分析笔记本

小明的数据分析笔记本 公众号 主要分享：1、R语言和python做数据分析和数据可视化的简单小例子；2、园艺植物相关转录组学、基因组学、群体遗传学文献阅读笔记；3、生物信息学入门学习资料及自己的学习笔记！

微信公众号好像又有改动，如果没有将这个公众号设为星标的话，会经常错过公众号的推文，个人建议将 小明的数据分析笔记本 公众号添加星标，添加方法是

点开公众号的页面，右上角有三个点

image.png

点击三个点，会跳出界面

image.png

直接点击 设为星标 就可以了