Clonality

Clonality in immune cells refers to the proliferation of genetically identical cells derived from a single ancestor cell.

Table (Data format)

This is an example of a data format containing the necessary information for clonality visualizations. The table includes mock data specifically generated for this purpose.

library(data.table)
library(stringr)
library(reactable)

df1 <- fread("../inst/data/clonality1.txt") 


reactable(
  
  df1, 
  theme = reactableTheme(
    backgroundColor  = "transparent"
  )
)

Circular Packing

The packcircles package is the optimal choice for constructing circular packing charts in R.

It efficiently calculates the position of each bubble, facilitating the creation of these charts using ggplot2.

# libraries -------

library(packcircles)
library(ggplot2)
library(shadowtext)



df1 = df1 |> split(by = c("group1", "group2"))



df_plot = df1 |> 
  lapply(function(q) {
    
    dat.egg <- q$clonality |> 
      circleProgressiveLayout() |> 
      circleLayoutVertices(npoints = 100)
    
    dat.egg <- cbind(dat.egg, q[dat.egg$id]) 
    
    return(dat.egg)
    
  }) |>
  
  rbindlist()



df_plot$group1 = df_plot$group1 |> str_to_upper()

df_plot_l = df_plot[, by = .(sample, group1, group2, clonality, id), .(
  x = ( min(x) + max(x) ) / 2,
  y = ( min(y) + max(y) ) / 2
)]

df_plot_l$lbl = df_plot_l$clonality |> round(digits = 2) |> paste0("%")



df_plot |>
  ggplot(aes(x, y, group = id)) +
  
  geom_polygon(aes(fill = clonality), color = "grey30", linewidth = .25) +
  
  geom_shadowtext(
    data = df_plot_l[which(clonality >= 10)], inherit.aes = FALSE,
    aes(x, y, label = lbl, size = clonality),  
    color = "grey1", bg.color = "#d9e3f1", bg.r = .15
  ) +
  
  scale_fill_stepsn(
    colors = c('#00429d', '#73a2c6', '#ffffe0', '#f4777f', '#93003a'),
    limits = c(0, 100),
    guide = guide_colorbar(
      title.position = "left",
      title.theme = element_text(angle = 90, hjust = 0),
      barheight = unit(7, "lines"),
      barwidth = unit(1.5, "lines")
    )
  ) +
  
  scale_size_continuous(guide = "none", range = c(1, 4)) +
  
  facet_grid(rows = vars(group2), cols = vars(group1), switch = "y") +
  
  coord_equal() +
  
  theme_minimal() +
  
  theme(
    strip.text.x.top = element_text(face = "bold", margin = margin(b = 10)),
    strip.text.y.left = element_text(face = "bold", margin = margin(r = 10)),
    
    axis.title = element_blank(),
    axis.text = element_blank(),
    
    panel.spacing = unit(1, "lines"),
    
    panel.grid.major = element_line(linewidth = .35),
    panel.grid.minor = element_line(linewidth = .25, linetype = "dashed"),
    
    plot.margin = margin(20, 20, 20, 20),
    
    plot.background = element_rect(fill = "transparent", color = NA)
    
  )