view_plate visualization enhancements: more than just text

[seaaan]

http://www.r-bloggers.com/plotting-microtiter-plate-maps/

[seaaan]

page 9

splots

[seaaan]

library(plateR)
library(dplyr)
library(ggplot2)

plot_plate <- function(plate, column) {
  to_plot <- plate %>% 
    mutate(RowId = substr(Wells, 1, 1), 
      ColId = as.numeric(substr(Wells, 2, 3))) %>% 
    mutate(RowId = factor(RowId, levels = rev(unique(RowId)))) 

  ggplot(to_plot, aes(x = ColId, y = RowId)) + 
    geom_tile(aes_string(fill = column), height = 0.9, width = 0.9) +
    scale_x_continuous(breaks = 1:max(to_plot$ColId)) +
    xlab(NULL) + ylab(NULL)
}

d <- read_plate(system.file("extdata", "example-1.csv", package = "plateR"))

plot_plate(d, "Killing")
plot_plate(d, "log10(Concentration)") + labs(fill = "Concentration")
plot_plate(d, "log10(Concentration)") + scale_fill_distiller(direction = 1) + 
  labs(fill = "Concentration")

Output from third example call:

[jooolia]

I think this is great! Indeed this way you could get a quick view of the data in plate format which could be very helpful for troubleshooting.

[seaaan]

Mapped to size instead:

plot_bubbles <- function(plate, column) {
   to_plot <- plate %>% 
      mutate(RowId = substr(Wells, 1, 1), 
         ColId = as.numeric(substr(Wells, 2, 3))) %>% 
      mutate(RowId = factor(RowId, levels = rev(unique(RowId)))) 

   ggplot(to_plot, aes(x = ColId, y = RowId)) + 
      geom_point(aes_string(size = column), shape = 1) +
      scale_x_continuous(breaks = 1:max(to_plot$ColId)) +
      xlab(NULL) + ylab(NULL)
}

d <- read_plate(system.file("extdata", "example-1.csv", package = "plateR"))

plot_bubbles(d, "Killing")