如何将此堆叠条形图转换为 R 中的圆形 plot？

Question

I want to convert this stacked barplot to a circular plot in R.

but the script here is just for grouped bar plots (as you can see at the center of the circle: A,B,C,D).

How can I convert this stacked barplot to a circular plot?

Here is my data:

   dput(df.bar)
structure(list(`Gene name` = c("Gene1", "Gene1", "Gene1", "Gene1", 
"Gene2", "Gene2", "Gene2", "Gene2", "Gene3", "Gene3", "Gene3", 
"Gene3", "Gene4", "Gene4", "Gene4", "Gene4", "Gene5", "Gene5", 
"Gene5", "Gene5", "Gene6", "Gene6", "Gene6", "Gene6", "Gene7", 
"Gene7", "Gene7", "Gene7", "Gene8", "Gene8", "Gene8", "Gene8", 
"Gene9", "Gene9", "Gene9", "Gene9", "Gene10", "Gene10", "Gene10", 
"Gene10", "Gene11", "Gene11", "Gene11", "Gene11", "Gene12", "Gene12", 
"Gene12", "Gene12", "Gene13", "Gene13", "Gene13", "Gene13", "Gene14", 
"Gene14", "Gene14", "Gene14", "Gene15", "Gene15", "Gene15", "Gene15", 
"Gene16", "Gene16", "Gene16", "Gene16"), `Alteration Frequency` = c(0, 
0.090991811, 2.183803458, 0.636942675, 0, 0.181983621, 1.091901729, 
0.363967243, 0, 0.454959054, 0.727934486, 0.727934486, 0, 0, 
0.363967243, 0.454959054, 0, 0, 1.364877161, 1.000909918, 0, 
0.272975432, 1.910828025, 0, 0, 0, 1.000909918, 0.727934486, 
0.090991811, 0.454959054, 14.83166515, 0.727934486, 0, 0, 1.18289354, 
0.363967243, 0, 0, 0.818926297, 0.363967243, 0, 0, 4.458598726, 
1.000909918, 0, 0, 0.636942675, 0.181983621, 0, 0, 0.636942675, 
0.181983621, 0.090991811, 0, 9.099181074, 0.363967243, 0, 0.181983621, 
0.363967243, 0.272975432, 0, 0.272975432, 0.181983621, 0.363967243
), `Alteration Type` = c("Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation", "Multiple Alteration", "Deep deletion", 
"Amplification", "Point mutation")), class = "data.frame", row.names = c(NA, 
-64L))

Thanks for any help.

Answer 1

You could do:

library(ggplot2)
library(geomtextpath)

ggplot(df.bar, aes(x = factor(`Gene name`, unique(`Gene name`)), 
                   y = `Alteration Frequency`, 
                   fill = `Alteration Type`)) +
  annotate('textsegment', label = c("0", "1", "2"), x = c(-Inf, -Inf, -Inf), 
           xend = c(Inf, Inf, Inf), y = c(0, 1, 2), yend = c(0, 1, 2),
         linewidth = 0.2, linecolour = 'gray50', hjust = 0.015) +
  geom_hline(yintercept = c(0.5, 1.5), size = 0.2, colour = 'gray75') +
  geom_col(width = 0.5, position = position_stack(), alpha = 0.8) +
  coord_polar(start = -pi/30) +
  ylim(c(-2, 2.2)) +
  annotate('segment', x = 1:16, xend = 1:16, y = rep(-1, 16),
           yend = rep(-0.6, 16), color = 'gray75') +
  annotate('text', x = 0, y = -2, label = 'Gene', size = 8,
           color = 'gray50') +
  annotate('textsegment', label = 1:16, 
           x = -0.3 + 1:16, xend = 0.3 + 1:16, y = rep(-0.1, 16), 
           yend = rep(-0.1, 16), vjust = 1.2, color = 'gray50') +
  theme_void() +
  scale_fill_brewer("Alteration Type", palette = 'Set2') +
  labs(title = 'Alteration Frequency') +
  theme(plot.title.position = 'panel',
        plot.title = element_text(hjust = 0.5, vjust = -10))