I have 7 different data points for virus concentration collected at 3 different time points. How do I graph this with error bars in R?

Question

I collected seven different samples containing varying concentrations of the Kunjin Virus.

• 3 samples are from the 24 hour time point: 667, 1330, 1670
• 2 samples are from the 48 hour time point: 323000, 590000
• 2 samples are from the 72 hour time point: 3430000, 4670000

How do I create a dotplot reflecting this data including error bars in R? I'm using ggplot2.

My code so far is:

data1 <-data.frame(hours, titer)
ggplot(data1, aes(x=hours, y=titer, colour = hours)) + geom_point()

Answer 1

I would suggest you next approach. If you want error bars you can compute it based on mean and standard deviation. In the next code is sketched the way to do that. I have used one standard deviation but you can set any other value. Also as you want to see different samples, I have used facet_wrap(). Here the code:

library(ggplot2)
library(dplyr)
#Data
df <- data.frame(sample=c(rep('24 hour',3),rep('48 hour',2),rep('72 hour',2)),
                 titer=c(667, 1330, 1670,323000, 590000,3430000, 4670000),
                 stringsAsFactors = F)
#Compute error bars
df <- df %>% group_by(sample) %>% mutate(Mean=mean(titer),SD=sd(titer))
#Plot
ggplot(df,aes(x=sample,y=titer,color=sample,group=sample))+
  geom_errorbar(aes(ymin=Mean-SD,ymax=Mean+SD),color='black')+
  geom_point()+
  scale_y_continuous(labels = scales::comma)+
  facet_wrap(.~sample,scales='free')

Output:

If you have a common y-axis scale, you can try this:

#Plot 2
ggplot(df,aes(x=sample,y=titer,color=sample,group=sample))+
  geom_errorbar(aes(ymin=Mean-SD,ymax=Mean+SD),color='black')+
  geom_point()+
  scale_y_continuous(labels = scales::comma)+
  facet_wrap(.~sample,scales = 'free_x')

Output: