rcirclize
Add percentage labels inside bars in circos.barplot in Circlize
I was able to create a stacked bar chart like this:
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()
How can I additionally add text for the percentage of each bar in the middle of the bar? I'd like to display the percentages as rounded to an integer, with percentages of 0 or 1 omitted.
Solution
I figured it out by modifying the code of the circos.barplot function.
The labels are drawn in a second loop after the rectangles so that the rectangles are not drawn over the labels.
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$order],]
circos.clear()
png("a.png",w=2500,h=2500,res=300)
circos.par(cell.padding=c(0,0,0,0),gap.degree=5,points.overflow.warning=F)
circos.initialize("a",xlim=c(0,nrow(t)))
circos.track(ylim=c(0,1),bg.border=NA,track.height=.28,track.margin=c(.01,0),
panel.fun=function(x,y)for(i in 1:nrow(t))circos.text(i-.5,0,labels[i],adj=c(0,.5),facing="clockwise",niceFacing=T,cex=.65,col=labelcolor[cut[labels[i]]]))
circos.track(ylim=c(0,1),track.margin=c(0,0),track.height=.35,bg.lty=0,panel.fun=function(x,y){
mat=as.matrix(t)
pos=1:nrow(mat)-.5
barwidth=1
for(i in 1:ncol(mat)){
seq1=rowSums(mat[,seq(i-1),drop=F])
seq2=rowSums(mat[,seq(i),drop=F])
circos.rect(pos-barwidth/2,if(i==1){0}else{seq1},pos+barwidth/2,seq2,col=barcolor[i],border="gray20",lwd=.1)
}
for(i in 1:ncol(mat)){
seq1=rowSums(mat[,seq(i-1),drop=F])
seq2=rowSums(mat[,seq(i),drop=F])
lab=round(100*t[,i])
lab[lab<=1]=""
circos.text(pos,if(i==1){seq1/2}else{seq1+(seq2-seq1)/2},labels=lab,col="gray10",cex=.4,facing="downward")
}
})
circos.track(ylim=c(0,attr(dend,"height")),bg.border=NA,track.margin=c(0,.0015),track.height=.35,panel.fun=function(x,y)circos.dendrogram(dend))
circos.clear()
dev.off()
- How can I download GADM data in R?
- Use dplyr to compute "streaks" in column of data
- Count empty strings?
- How to lookup and sum multiple columns in R
- Is there a way to make the bars' colors conditional to the column?
- How to assign values to a df$column from another df using conditions in R
- Is there a way to read Qlikview data object using R and perform an statistical operation and return results to Qlikview?
- R: Extracting characters from string vectors to data frame rows
- Else if statement to create a new column
- Calculate percentage in a data frame R
- How can I calculate sums of multiple columns without them being summed together into 1 column?
- How to convert a binary file with extension .GRD to .TXT in R?
- How to specify the size of a graph in ggplot2 independent of axis labels
- Using sqldf filter and group by in r dynamically
- Grouping data and reassembling rows as columns
- Coordinates of current mouse position on leaflet map with shiny
- read_csv drops 'f' from end of string
- wes_palettes: How to obtain color hex codes from a wesanderson palette when it set to continuous with more than the predefined colors
- ggplot2 change axis limits for each individual facet panel
- Mixing Rcpp modules and Rcpp::export
- How to create a forest plot that uses estimates obtained from ClubSandwich?
- how to include an abstract in a Rmd file
- Difference between ntile and cut and then quantile() function in R
- Install with devtools::install_github() fails to detect build tools
- How to assign geometry type "polygons" to SpatVector with "null" geometry type using the terra package in R?
- Fitting of nls model in R - manual versus brute force issues
- Likelihood ratio when the difference in the log-likelihood is a large negative number
- How to tally occurrences of same value across columns in R?
- Apply function rowwise() using column names to identify function arguments using mutate()
- writing multiple data frames into the same excel file in R