r - 在 Circlize 的 circos.barplot 中的条形内添加百分比标签

Question

我能够创建一个这样的堆积条形图：

library(circlize)
library(vegan) # for `reorder.hclust` (may be masked by the library `seriation`)
library(dendextend) # for `color_branches`

t=read.table(text="Kalmyk 0.119357 0.725057 0.000010 0.037803 0.117774
Kyrgyz_China 0.039367 0.512079 0.230150 0.095038 0.123366
Altaian_Chelkan 0.034095 0.000010 0.919478 0.000010 0.046407
Azeri 0.051638 0.004671 0.010727 0.902646 0.030318
Uzbek 0.102725 0.273261 0.001854 0.452126 0.170033
Salar 0.000010 0.539636 0.460334 0.000010 0.000010
Tatar_Kazan 0.113456 0.057026 0.000010 0.099336 0.730171
Tatar_Siberian 0.251376 0.221389 0.000010 0.077505 0.449721
Finnish 0.007214 0.000010 0.000010 0.015174 0.977592
Yakut 0.505434 0.473202 0.000010 0.002914 0.018440
Mansi 0.572791 0.000010 0.000010 0.000010 0.427179
Altaian 0.222424 0.335614 0.358801 0.032694 0.050468
Shor_Mountain 0.233984 0.000010 0.724596 0.000010 0.041400
Chuvash 0.180171 0.011056 0.000010 0.006462 0.802301
Enets 0.920409 0.000010 0.000010 0.000010 0.079561
Yukagir_Tundra 0.710359 0.289611 0.000010 0.000011 0.000010
Kyrgyz_Tajikistan 0.104000 0.563708 0.000010 0.125799 0.206483
Khakass_Kachin 0.254253 0.416760 0.174200 0.005262 0.149525
Tuvinian 0.448940 0.448899 0.000010 0.031803 0.070348
Besermyan 0.209841 0.001487 0.000010 0.000460 0.788202
Nogai_Astrakhan 0.062497 0.463590 0.000010 0.183203 0.290701
Todzin 0.725173 0.257670 0.000010 0.005836 0.011312
Kazakh 0.067027 0.518213 0.087979 0.114550 0.212231
Tofalar 0.815599 0.110299 0.000010 0.009693 0.064398
Karakalpak 0.009983 0.316964 0.389103 0.158275 0.125676
Estonian 0.000010 0.000010 0.000010 0.004409 0.995561
Dolgan 0.694025 0.255361 0.000010 0.049624 0.000979
Tatar_Siberian_Zabolotniye 0.521637 0.020132 0.000010 0.000010 0.458212
Uyghur 0.043578 0.486742 0.000010 0.318983 0.150687
Udmurt 0.256391 0.000010 0.001010 0.000010 0.742579
Evenk_FarEast 0.241328 0.606202 0.000010 0.000010 0.152451
Selkup 0.804662 0.000010 0.000010 0.000010 0.195308
Kumyk 0.060751 0.000112 0.000010 0.823905 0.115222
Hungarian 0.000010 0.000010 0.000010 0.244311 0.755659
Tubalar 0.159517 0.009457 0.802778 0.000010 0.028238
Turkmen 0.123631 0.226543 0.000010 0.529793 0.120023
Karelian 0.012854 0.000010 0.000010 0.000010 0.987116
Kazakh_China 0.074285 0.573009 0.152931 0.069362 0.130412
Mongol 0.033174 0.847004 0.025135 0.005178 0.089509
Daur 0.000010 0.995215 0.000010 0.000010 0.004755
Evenk_Transbaikal 0.611414 0.388556 0.000010 0.000010 0.000010
Nogai_Karachay_Cherkessia 0.119988 0.120774 0.000010 0.617261 0.141967
Veps 0.026887 0.000010 0.000010 0.000010 0.973083
Even 0.441349 0.278457 0.000010 0.015239 0.264946
Nganasan 0.999960 0.000010 0.000010 0.000010 0.000010
Bashkir 0.114088 0.056493 0.251488 0.030390 0.547542
Xibo 0.000010 0.985541 0.000010 0.000362 0.014077
Khakass 0.202707 0.171413 0.530905 0.007675 0.087300
Shor_Khakassia 0.258218 0.000010 0.694889 0.000010 0.046873
Nanai 0.105903 0.894067 0.000010 0.000010 0.000010
Buryat 0.064420 0.848458 0.017066 0.001696 0.068360
Yukagir_Forest 0.379416 0.096266 0.000010 0.003580 0.520728
Karachai 0.067138 0.004534 0.000010 0.798982 0.129336
Mordovian 0.022303 0.001193 0.000010 0.025251 0.951243
Turkish_Balikesir 0.092314 0.038550 0.000010 0.804964 0.064163
Turkish 0.040918 0.012255 0.000010 0.873179 0.073639
Kyrgyz_Kyrgyzstan 0.090129 0.607265 0.000010 0.122885 0.179711
Balkar 0.075115 0.000010 0.000010 0.829730 0.095136
Gagauz 0.000010 0.027887 0.015891 0.601619 0.354593
Nogai_Stavropol 0.070584 0.403817 0.000010 0.244701 0.280888
Negidal 0.248518 0.751452 0.000010 0.000010 0.000010
Tatar_Mishar 0.066112 0.037441 0.010377 0.138008 0.748062",row.names=1)

hc=reorder(hclust(dist(t)),-as.matrix(t)%*%seq(ncol(t))^2)

labelcolor=hcl(c(260,90,120,60,0,210,180,310)+15,60,70)
barcolor=hcl(c(310,260,120,60,210)+15,60,70)

labels=hc$labels[hc$order]
cut=cutree(hc,8)
dend=color_branches(as.dendrogram(hc),k=length(unique(cut)),
  col=labelcolor[unique(cut[labels])])

circos.clear()
png("a.png",w=2000,h=2000,res=200)
circos.par(cell.padding=c(0,0,0,0))
circos.initialize("a",xlim=c(0,nrow(t)))

circos.track(ylim=c(0,1),track.height=.2,track.margin=c(0,0),bg.border=NA,
  panel.fun=function(x,y)for(i in 1:nrow(t))circos.text(i-.5,0,labels[i],adj=c(0,.5),
    facing="clockwise",niceFacing=T,cex=.75,col=labelcolor[cut[labels[i]]]))

circos.track(ylim=c(0,1),track.height=.3,track.margin=c(0,.01),bg.border=NA,
  panel.fun=function(x,y)circos.barplot(as.matrix(t)[hc$order,],-.5+1:nrow(t),
    col=barcolor,bar_width=1,lwd=.3,border="gray20"))

circos.track(ylim=c(0,attr(dend,"height")),track.height=.4,track.margin=c(0,0),
  bg.border=NA,panel.fun=function(x,y)circos.dendrogram(dend))

circos.clear()
dev.off()

如何在栏的中间为每个栏的百分比另外添加文本？我想将百分比显示为四舍五入的整数，省略 0 或 1 的百分比。

Answer 1

我通过修改circos.barplot函数的代码来解决这个问题。

标签在矩形之后的第二个循环中绘制，因此矩形不会绘制在标签上。

library(circlize)
library(vegan) # for reorder.hclust (may be masked by `seriation`)
library(dendextend) # for color_branches

t=read.table(text="Kalmyk 0.119357 0.725057 0.000010 0.037803 0.117774
Kyrgyz_China 0.039367 0.512079 0.230150 0.095038 0.123366
Altaian_Chelkan 0.034095 0.000010 0.919478 0.000010 0.046407
Azeri 0.051638 0.004671 0.010727 0.902646 0.030318
Uzbek 0.102725 0.273261 0.001854 0.452126 0.170033
Salar 0.000010 0.539636 0.460334 0.000010 0.000010
Tatar_Kazan 0.113456 0.057026 0.000010 0.099336 0.730171
Tatar_Siberian 0.251376 0.221389 0.000010 0.077505 0.449721
Finnish 0.007214 0.000010 0.000010 0.015174 0.977592
Yakut 0.505434 0.473202 0.000010 0.002914 0.018440
Mansi 0.572791 0.000010 0.000010 0.000010 0.427179
Altaian 0.222424 0.335614 0.358801 0.032694 0.050468
Shor_Mountain 0.233984 0.000010 0.724596 0.000010 0.041400
Chuvash 0.180171 0.011056 0.000010 0.006462 0.802301
Enets 0.920409 0.000010 0.000010 0.000010 0.079561
Yukagir_Tundra 0.710359 0.289611 0.000010 0.000011 0.000010
Kyrgyz_Tajikistan 0.104000 0.563708 0.000010 0.125799 0.206483
Khakass_Kachin 0.254253 0.416760 0.174200 0.005262 0.149525
Tuvinian 0.448940 0.448899 0.000010 0.031803 0.070348
Besermyan 0.209841 0.001487 0.000010 0.000460 0.788202
Nogai_Astrakhan 0.062497 0.463590 0.000010 0.183203 0.290701
Todzin 0.725173 0.257670 0.000010 0.005836 0.011312
Kazakh 0.067027 0.518213 0.087979 0.114550 0.212231
Tofalar 0.815599 0.110299 0.000010 0.009693 0.064398
Karakalpak 0.009983 0.316964 0.389103 0.158275 0.125676
Estonian 0.000010 0.000010 0.000010 0.004409 0.995561
Dolgan 0.694025 0.255361 0.000010 0.049624 0.000979
Tatar_Siberian_Zabolotniye 0.521637 0.020132 0.000010 0.000010 0.458212
Uyghur 0.043578 0.486742 0.000010 0.318983 0.150687
Udmurt 0.256391 0.000010 0.001010 0.000010 0.742579
Evenk_FarEast 0.241328 0.606202 0.000010 0.000010 0.152451
Selkup 0.804662 0.000010 0.000010 0.000010 0.195308
Kumyk 0.060751 0.000112 0.000010 0.823905 0.115222
Hungarian 0.000010 0.000010 0.000010 0.244311 0.755659
Tubalar 0.159517 0.009457 0.802778 0.000010 0.028238
Turkmen 0.123631 0.226543 0.000010 0.529793 0.120023
Karelian 0.012854 0.000010 0.000010 0.000010 0.987116
Kazakh_China 0.074285 0.573009 0.152931 0.069362 0.130412
Mongol 0.033174 0.847004 0.025135 0.005178 0.089509
Daur 0.000010 0.995215 0.000010 0.000010 0.004755
Evenk_Transbaikal 0.611414 0.388556 0.000010 0.000010 0.000010
Nogai_Karachay_Cherkessia 0.119988 0.120774 0.000010 0.617261 0.141967
Veps 0.026887 0.000010 0.000010 0.000010 0.973083
Even 0.441349 0.278457 0.000010 0.015239 0.264946
Nganasan 0.999960 0.000010 0.000010 0.000010 0.000010
Bashkir 0.114088 0.056493 0.251488 0.030390 0.547542
Xibo 0.000010 0.985541 0.000010 0.000362 0.014077
Khakass 0.202707 0.171413 0.530905 0.007675 0.087300
Shor_Khakassia 0.258218 0.000010 0.694889 0.000010 0.046873
Nanai 0.105903 0.894067 0.000010 0.000010 0.000010
Buryat 0.064420 0.848458 0.017066 0.001696 0.068360
Yukagir_Forest 0.379416 0.096266 0.000010 0.003580 0.520728
Karachai 0.067138 0.004534 0.000010 0.798982 0.129336
Mordovian 0.022303 0.001193 0.000010 0.025251 0.951243
Turkish_Balikesir 0.092314 0.038550 0.000010 0.804964 0.064163
Turkish 0.040918 0.012255 0.000010 0.873179 0.073639
Kyrgyz_Kyrgyzstan 0.090129 0.607265 0.000010 0.122885 0.179711
Balkar 0.075115 0.000010 0.000010 0.829730 0.095136
Gagauz 0.000010 0.027887 0.015891 0.601619 0.354593
Nogai_Stavropol 0.070584 0.403817 0.000010 0.244701 0.280888
Negidal 0.248518 0.751452 0.000010 0.000010 0.000010
Tatar_Mishar 0.066112 0.037441 0.010377 0.138008 0.748062",row.names=1)

hc=hclust(dist(t))
hc=reorder(hc,-(t[,1]+t[,2]-t[,4]-2*t[,5]))

labelcolor=hcl(c(260,90,120,60,0,210,180,310)+15,60,70)
barcolor=hcl(c(310,260,120,60,210)+15,60,70)

labels=hc$labels[hc$order]
cut=cutree(hc,8)
dend=color_branches(as.dendrogram(hc),k=length(unique(cut)),col=labelcolor[unique(cut[labels])])
t=t[hc$labels[hc$order],]

circos.clear()
png("a.png",w=2500,h=2500,res=300)
circos.par(cell.padding=c(0,0,0,0),gap.degree=5,points.overflow.warning=F)
circos.initialize("a",xlim=c(0,nrow(t)))

circos.track(ylim=c(0,1),bg.border=NA,track.height=.28,track.margin=c(.01,0),
  panel.fun=function(x,y)for(i in 1:nrow(t))circos.text(i-.5,0,labels[i],adj=c(0,.5),facing="clockwise",niceFacing=T,cex=.65,col=labelcolor[cut[labels[i]]]))

circos.track(ylim=c(0,1),track.margin=c(0,0),track.height=.35,bg.lty=0,panel.fun=function(x,y){
  mat=as.matrix(t)
  pos=1:nrow(mat)-.5
  barwidth=1
  for(i in 1:ncol(mat)){
    seq1=rowSums(mat[,seq(i-1),drop=F])
    seq2=rowSums(mat[,seq(i),drop=F])
    circos.rect(pos-barwidth/2,if(i==1){0}else{seq1},pos+barwidth/2,seq2,col=barcolor[i],border="gray20",lwd=.1)
  }
  for(i in 1:ncol(mat)){
    seq1=rowSums(mat[,seq(i-1),drop=F])
    seq2=rowSums(mat[,seq(i),drop=F])
    lab=round(100*t[,i])
    lab[lab<=1]=""
    circos.text(pos,if(i==1){seq1/2}else{seq1+(seq2-seq1)/2},labels=lab,col="gray10",cex=.4,facing="downward")
  }
})

circos.track(ylim=c(0,attr(dend,"height")),bg.border=NA,track.margin=c(0,.0015),track.height=.35,panel.fun=function(x,y)circos.dendrogram(dend))

circos.clear()
dev.off()