Advanced chord diagram with R and circlize

Chord diagram from adjacency matrix

The circlize package developped by Zuguang Gu is the best way to build chord diagram in R. The chord diagram section of the gallery provides a step by step introduction to it.

This example explains how to build a highly customized chord diagram, adding links manually thanks to the circos.link() function.

Note that the library also offers a chordDiagram() functions that builds everything automatically, but offers less customization. (See it here.)

Important: This example has been found on stackoverflow, made by Jazzuro.

### You need several libraries library(circlize) library(migest) library(dplyr) ### Make data m <- data.frame(order = 1:6, country = c("Ausralia", "India", "China", "Japan", "Thailand", "Malaysia"), V3 = c(1, 150000, 90000, 180000, 15000, 10000), V4 = c(35000, 1, 10000, 12000, 25000, 8000), V5 = c(10000, 7000, 1, 40000, 5000, 4000), V6 = c(7000, 8000, 175000, 1, 11000, 18000), V7 = c(70000, 30000, 22000, 120000, 1, 40000), V8 = c(60000, 90000, 110000, 14000, 30000, 1), r = c(255,255,255,153,51,51), g = c(51, 153, 255, 255, 255, 255), b = c(51, 51, 51, 51, 51, 153), stringsAsFactors = FALSE) df1 <- m[, c(1,2, 9:11)] m <- m[,-(1:2)]/1e04 m <- as.matrix(m[,c(1:6)]) dimnames(m) <- list(orig = df1$country, dest = df1$country) #Sort order of data.frame and matrix for plotting in circos df1 <- arrange(df1, order) df1$country <- factor(df1$country, levels = df1$country) m <- m[levels(df1$country),levels(df1$country)] ### Define ranges of circos sectors and their colors (both of the sectors and the links) df1$xmin <- 0 df1$xmax <- rowSums(m) + colSums(m) n <- nrow(df1) df1$rcol<-rgb(df1$r, df1$g, df1$b, max = 255) df1$lcol<-rgb(df1$r, df1$g, df1$b, alpha=200, max = 255) ### Plot sectors (outer part) par(mar=rep(0,4)) circos.clear() ### Basic circos graphic parameters circos.par(cell.padding=c(0,0,0,0), track.margin=c(0,0.15), start.degree = 90, gap.degree =4) ### Sector details circos.initialize(factors = df1$country, xlim = cbind(df1$xmin, df1$xmax)) ### Plot sectors circos.trackPlotRegion(ylim = c(0, 1), factors = df1$country, track.height=0.1, #panel.fun for each sector panel.fun = function(x, y) { #select details of current sector name = get.cell.meta.data("sector.index") i = get.cell.meta.data("sector.numeric.index") xlim = get.cell.meta.data("xlim") ylim = get.cell.meta.data("ylim") #text direction (dd) and adjusmtents (aa) theta = circlize(mean(xlim), 1.3)[1, 1] %% 360 dd <- ifelse(theta < 90 || theta > 270, "clockwise", "reverse.clockwise") aa = c(1, 0.5) if(theta < 90 || theta > 270) aa = c(0, 0.5) #plot country labels circos.text(x=mean(xlim), y=1.7, labels=name, facing = dd, cex=0.6, adj = aa) #plot main sector circos.rect(xleft=xlim[1], ybottom=ylim[1], xright=xlim[2], ytop=ylim[2], col = df1$rcol[i], border=df1$rcol[i]) #blank in part of main sector circos.rect(xleft=xlim[1], ybottom=ylim[1], xright=xlim[2]-rowSums(m)[i], ytop=ylim[1]+0.3, col = "white", border = "white") #white line all the way around circos.rect(xleft=xlim[1], ybottom=0.3, xright=xlim[2], ytop=0.32, col = "white", border = "white") #plot axis circos.axis(labels.cex=0.6, direction = "outside", major.at=seq(from=0,to=floor(df1$xmax)[i],by=5), minor.ticks=1, labels.away.percentage = 0.15) }) ### Plot links (inner part) ### Add sum values to df1, marking the x-position of the first links ### out (sum1) and in (sum2). Updated for further links in loop below. df1$sum1 <- colSums(m) df1$sum2 <- numeric(n) ### Create a data.frame of the flow matrix sorted by flow size, to allow largest flow plotted first df2 <- cbind(as.data.frame(m),orig=rownames(m), stringsAsFactors=FALSE) df2 <- reshape(df2, idvar="orig", varying=list(1:n), direction="long", timevar="dest", time=rownames(m), v.names = "m") df2 <- arrange(df2,desc(m)) ### Keep only the largest flows to avoid clutter df2 <- subset(df2, m > quantile(m,0.6)) ### Plot links for(k in 1:nrow(df2)){ #i,j reference of flow matrix i<-match(df2$orig[k],df1$country) j<-match(df2$dest[k],df1$country) #plot link circos.link(sector.index1=df1$country[i], point1=c(df1$sum1[i], df1$sum1[i] + abs(m[i, j])), sector.index2=df1$country[j], point2=c(df1$sum2[j], df1$sum2[j] + abs(m[i, j])), col = df1$lcol[i]) #update sum1 and sum2 for use when plotting the next link df1$sum1[i] = df1$sum1[i] + abs(m[i, j]) df1$sum2[j] = df1$sum2[j] + abs(m[i, j]) }

Contact

This document is a work by Yan Holtz. Any feedback is highly encouraged. You can fill an issue on Github, drop me a message on Twitter, or send an email pasting yan.holtz.data with gmail.com.