## See example RScript below. It has been annotated for clarity. 
## Please feel free to modify this as needed. Note that the ggplot2 
## and ggsignif are two separate packages that must be added to your
## library for this script to run. 

#### Load packages and example dataset ####
library(ggplot2)
library(tidyverse)
library(ggsignif)

J774A.1.Area <- read.csv(file = 'Cell Surface Area.csv')

#### Perform an ANOVA and post-hoc test. ####
Area.ANOVA <- aov(Cell.A ~ Treatment.A, data = J774A.1.Area)
summary(Area.ANOVA)

TukeyHSD(Area.ANOVA)

# Print your data. 
##                                            diff      lwr        upr     p adj
##Mock (MeOH)-Mock (1x PBS only)          -18.3315 -228.97271  192.30971 0.9992534
##LPS (500 ng/mL)-Mock (1x PBS only)      430.7079  220.06669  641.34911 0.0000008
##Nigericin (45 mins)-Mock (1x PBS only)  820.6452  610.00396 1031.28638 0.0000000
##Nigericin (2 hr)-Mock (1x PBS only)     593.4385  380.98915  805.88780 0.0000000
##LPS (500 ng/mL)-Mock (MeOH)             449.0394  238.39819  659.68061 0.0000003
##Nigericin (45 mins)-Mock (MeOH)         838.9767  628.33546 1049.61788 0.0000000
##Nigericin (2 hr)-Mock (MeOH)            611.7700  399.32065  824.21930 0.0000000
##Nigericin (45 mins)-LPS (500 ng/mL)     389.9373  179.29606  600.57848 0.0000097
##Nigericin (2 hr)-LPS (500 ng/mL)        162.7306  -49.71875  375.17990 0.2189068
##Nigericin (2 hr)-Nigericin (45 mins)   -227.2067 -439.65602  -14.75737 0.0296109

#### Set parameters for class and factor #### 
## This will make sure your conditions show up in the desired order when 
##graphing. It will otherwise sort according to alphabetical order. 
class(J774A.1.Area$Treatment.A)3
J774A.1.Area$Treatment.A = 
  factor(J774A.1.Area$Treatment.A, level = 
           c('Mock (1x PBS only)','Mock (MeOH)', 
             'LPS (500 ng/mL)','Nigericin (45 mins)','Nigericin (2 hr)'))
levels(J774A.1.Area$Treatment.A)
class

J774A.1.Area$Treatment.A <- as.factor(J774A.1.Area$Treatment.A, 
                     levels = c('Mock (1x PBS only)','Mock (MeOH)', 
                     'LPS (500 ng/mL)','Nigericin (45 mins)','Nigericin (2 hr)'))
head(J774A.1.Area)

level_order_area <- c('Mock (1x PBS only)','Mock (MeOH)', 
                      'LPS (500 ng/mL)','Nigericin (45 mins)','Nigericin (2 hr)')

#### Set parameters for the plot you want to create. #### 
## The following script will generate boxplots with a dot-plot overlaid. 
CellAreaPlot <- ggplot(J774A.1.Area, aes(x=factor(Treatment.A, level=level_order_area), 
                           y=Cell.A,fill=Treatment.A)) + 
  geom_boxplot(outlier.colour="red", outlier.shape=16,
               outlier.size=2.5, notch=FALSE, outlier.alpha = 0.1) +
  labs(y = bquote('Cell surface area'~(μm^2)), x = "Treatment group") +
  scale_fill_manual(values = c("#FAE6FA","#D8BFD8","#B768A2","#6C3082","#301934")) +
  theme(legend.position="none") + 
  geom_dotplot(binaxis='y', stackdir='center', dotsize=0.3, stackratio=1.5)
CellAreaPlot

# Print your plot; check for any errors.  
CellAreaPlot

# If you want, annotate your plot to indicate the significance of your measurements.  
CellAreaPlot + geom_signif(y_position = c(750,1450,1950, 2070, 2250), 
               xmin = c(1,1,3, 4,3), 
               xmax = c(2,3,4,5,5),
               annotation = c("ns","***","***","**","ns"), tip_length = 0.01)