Hi Bogdan,

In R you can create a plot like the one you decribe with karyoploteR.

Here's a small example with random data (random positions in the genome created with createRandomRegions from the package regioneR). You can add additional data, use a different genome, change color and sizes and in general customize the plot in many ways using this package. You can find a short tutorial and some more complex examples at karyoploteR's tutorial and examples page.

library(regioneR)
library(karyoploteR)

set.seed(12345)

#Create example data
gains <- createRandomRegions(nregions = 10, length.mean = 10e6, length.sd = 10e6, genome = "hg19", mask=NULL)
losses <- createRandomRegions(nregions = 10, length.mean = 10e6, length.sd = 10e6, genome = "hg19", mask=NULL)
snv <- createRandomRegions(nregions = 200, length.mean = 1, length.sd = 0, genome = "hg19", mask=NULL)
snv.cols <- sample(x = c("red", "blue", "gold", "orchid", "palegreen"), 200, replace = TRUE)

sv.origin <- createRandomRegions(nregions = 10, length.mean = 1, length.sd = 0, genome = "hg19", mask=NULL)
sv.end <- createRandomRegions(nregions = 10, length.mean = 1, length.sd = 0, genome = "hg19", mask=NULL)

#Create the plot
png("example.png", width=1500, height=1500)
kp <- plotKaryotype(cex=2)

#Plot the SNVs as points (use different colors to represent different mutation types)
kpPoints(kp, data=snv, y=0, r0=0.1, r1=0.1, col=snv.cols, cex = 2)

#plot gains (orange) and losses (green)
kpPlotRegions(kp, data=gains, r0=0.3, r1=0.8, col="#FF7744", border = NA)
kpPlotRegions(kp, data=losses, r0=0.3, r1=0.8, col="#77FF44", border = NA)

#Plot the links representing the SVs
kpPlotLinks(kp, data=sv.origin, data2 = sv.end, col="black")

dev.off()

And that will create this image

Hope this helps

Dear Benat, thank you also for the example below that you have graciously shared !

png("example_oneline.png", width=1500, height=800)
pp <- getDefaultPlotParams(plot.type=3)
pp$data2height <- 50
kp <- plotKaryotype(cex=2, plot.type=3, plot.params = pp, labels.plotter = NULL, ideogram.plotter = NULL)
kpAddCytobandsAsLine(kp)
kpAddChromosomeNames(kp, srt=45, cex=2)

#Plot the SNVs as points (use different colors to represent different mutation types)
kpPoints(kp, data=snv, y=0, r0=0.1, r1=0.1, col=snv.cols, cex = 2, data.panel = 2)

#plot gains (orange) and losses (green)
kpPlotRegions(kp, data=gains, r0=0.3, r1=1, col="#FF7744", border = NA, data.panel=2)
kpPlotRegions(kp, data=losses, r0=0.3, r1=1, col="#77FF44", border = NA, data.panel = 2)

#Plot the links representing the SVs
kpPlotLinks(kp, data=sv.origin, data2 = sv.end, col="black")

dev.off()