# input file should be in the format: Treatment groups, Values
  # For Example: 
    # Treatment   Value
    # Control     #####
    # Treatment   #####
    # Control     #####
    # Treatment 2 #####
    # ETC.


library(readxl)
Plot_input <- read_excel("")
# Insert file location in "" in the brackets

library(ggplot2)
library(dplyr)
library(plotrix)

Plot_input$Treatment=factor(Plot_input$Treatment,levels = c())
# insert row names in c() brackets: "Control", "Treatment group", "Treatment group 2", etc

grouped_df2<-group_by()
# Insert into brackets: Plot_input, Treatment, value
summarised_df2<-summarise_each(grouped_df2,funs(mean=mean,std_error=std.error))
limits <- aes(ymax = mean + std_error, ymin=mean-std_error)

ggplot(Plot_input,mapping=aes(x=, y=, color=Treatment)) +
  #Insert column name: I.E. X= Treatment, y= Value
  geom_point(position = position_jitter(width = .2)) +
  # You can change the point jitter by adjusting the vales
  scale_color_manual (values = c())+
  # Insert the color you want into c(): I.E. using hex color codes: "Control" = '#b2a5cd'
  # It will create a legend in the order you write the treatment groups.
  stat_summary(fun = mean, 
               fun.min = function(x) mean(x) - sd(x)/sqrt(length(x)), 
               fun.max = function(x) mean(x) + sd(x)/sqrt(length(x)),
               geom = 'errorbar',  width = 0.25,color="black")+
  # Will create a point at the mean +/- SEM
  # You can change the shape color and size of the point by adjusting the vales.
  xlab('Treatment') +
  theme_classic() +
  stat_summary(fun=mean, na.rm = TRUE, shape = "diamond", color = "black") + 
  # You can change the shape color and size of the point by adjusting the vales
  scale_y_continuous(breaks = seq(), limits = c())
  # breaks = seq(X, Y, Z) set the Y scale: X= lower limit labeled,  Y = upper limit labeled, Z = Divisions in between
  # limits = c(X, Y) set the Y scale: X= lower limit displayed,  Y = upper limit displayed