How to make 1 the highest value for a bar chart in ggplot

Question

I am trying to graph ct values derived from a PCR. A high ct value indicates low levels of virus and a low ct indicates high levels of virus. I would like this reflected in my data, i.e. the scale to start at 40, then go up to 0, so that 0 would be the highest value on the x axis. I know a similar question has been asked before, however I tried the code provided in the answer and found it didn't work with my data set. Here is the code I am using to make my graph in ggplot:

ggplot(data=data, aes(x = Virus.hpi, y=ct, fill=Virus.hpi)) + 
  scale_fill_manual(values = c("BTV-1 0hpsi" = "blue", 
                               "BTV-1 72hpsi" = "blue", 
                               "BTV-8 0hpsi" = "purple", 
                               "BTV-8 72hpsi" = "purple")) + 
  stat_summary(fun = mean, geom = "bar") + 
  stat_summary(fun.data = mean_cl_normal, geom = "errorbar", width = 0.3) + 
  geom_point(data=data1,  aes(x = Virus.hpi, y=ct, fill=Virus.hpi))

I am working in Rstudio. Thanks.

Answer 1

ggplot2 allows you to reverse the scales, simply add scale_y_reverse() to your plot:

ggplot(data=data, aes(x = Virus.hpi, y=ct, fill=Virus.hpi)) + 
  scale_fill_manual(values = c("BTV-1 0hpsi" = "blue", 
                               "BTV-1 72hpsi" = "blue", 
                               "BTV-8 0hpsi" = "purple", 
                               "BTV-8 72hpsi" = "purple")) + 
  stat_summary(fun = mean, geom = "bar") + 
  stat_summary(fun.data = mean_cl_normal, geom = "errorbar", width = 0.3) + 
  geom_point(data=data1,  aes(x = Virus.hpi, y=ct, fill=Virus.hpi)) +
  scale_y_reverse()

alternatively, you can set the limits of your y-axis in reverse order:

ggplot(data=data, aes(x = Virus.hpi, y=ct, fill=Virus.hpi)) + 
  scale_fill_manual(values = c("BTV-1 0hpsi" = "blue", 
                               "BTV-1 72hpsi" = "blue", 
                               "BTV-8 0hpsi" = "purple", 
                               "BTV-8 72hpsi" = "purple")) + 
  stat_summary(fun = mean, geom = "bar") + 
  stat_summary(fun.data = mean_cl_normal, geom = "errorbar", width = 0.3) + 
  geom_point(data=data1,  aes(x = Virus.hpi, y=ct, fill=Virus.hpi)) +
  ylim(40, 0)

Note that this will, however, extend your bars downwards.

Answer 2

Maybe you can subtract 40 with your ct value, to get a kind of "reversed" ct values. Then reverse the labelling in scale_y_continuous().

library(ggplot2)
library(dplyr)

data %>% mutate(ct = 40 - ct) %>% 
ggplot(aes(x = Virus.hpi, y=ct, fill=Virus.hpi)) + 
  scale_fill_manual(values = c("BTV-1 0hpsi" = "blue", 
                               "BTV-1 72hpsi" = "blue", 
                               "BTV-8 0hpsi" = "purple", 
                               "BTV-8 72hpsi" = "purple")) + 
  stat_summary(fun = mean, geom = "bar") + 
  stat_summary(fun.data = mean_cl_normal, geom = "errorbar", width = 0.3) + 
  geom_point() +
  scale_y_continuous(breaks = seq(0, 40, 10), labels = rev(seq(0, 40, 10)))

dummy data for demonstration

structure(list(ct = c(35L, 30L, 22L, 38L), Virus.hpi = c("BTV-1 0hpsi", 
"BTV-1 72hpsi", "BTV-8 0hpsi", "BTV-8 72hpsi")), class = "data.frame", row.names = c(NA, 
-4L))

data
  ct    Virus.hpi
1 35  BTV-1 0hpsi
2 30 BTV-1 72hpsi
3 22  BTV-8 0hpsi
4 38 BTV-8 72hpsi