Prepare the data

ToothGrowth data sets are used :

# Convert the variable dose from a numeric to a factor variable
ToothGrowth$dose <- as.factor(ToothGrowth$dose)
head(ToothGrowth)

##    len supp dose
## 1  4.2   VC  0.5
## 2 11.5   VC  0.5
## 3  7.3   VC  0.5
## 4  5.8   VC  0.5
## 5  6.4   VC  0.5
## 6 10.0   VC  0.5

Make sure that the variable dose is converted as a factor variable using the above R script.

Basic stripcharts

library(ggplot2)
# Basic stripchart
ggplot(ToothGrowth, aes(x=dose, y=len)) + 
  geom_jitter()
# Change the position
# 0.2 : degree of jitter in x direction
p<-ggplot(ToothGrowth, aes(x=dose, y=len)) + 
  geom_jitter(position=position_jitter(0.2))
p
# Rotate the stripchart
p + coord_flip()

Choose which items to display :

p + scale_x_discrete(limits=c("0.5", "2"))

Change point shapes and size :

# Change point size
ggplot(ToothGrowth, aes(x=dose, y=len)) + 
  geom_jitter(position=position_jitter(0.2), cex=1.2)
# Change shape
ggplot(ToothGrowth, aes(x=dose, y=len)) + 
  geom_jitter(position=position_jitter(0.2), shape=17)

Read more on point shapes : ggplot2 point shapes

Add summary statistics on a stripchart

The function stat_summary() can be used to add mean/median points and more to a stripchart.

# stripchart with mean points
p + stat_summary(fun.y=mean, geom="point", shape=18,
                 size=3, color="red")
# stripchart with median points
p + stat_summary(fun.y=median, geom="point", shape=18,
                 size=3, color="red")

# Add basic box plot
ggplot(ToothGrowth, aes(x=dose, y=len)) + 
  geom_boxplot()+
  geom_jitter(position=position_jitter(0.2))
# Add notched box plot
ggplot(ToothGrowth, aes(x=dose, y=len)) + 
  geom_boxplot(notch = TRUE)+
  geom_jitter(position=position_jitter(0.2))
# Add violin plot
ggplot(ToothGrowth, aes(x=dose, y=len)) + 
  geom_violin(trim = FALSE)+
  geom_jitter(position=position_jitter(0.2))

p <- ggplot(ToothGrowth, aes(x=dose, y=len)) + 
    geom_jitter(position=position_jitter(0.2))
p + stat_summary(fun.data="mean_sdl", mult=1, 
                 geom="crossbar", width=0.5)
p + stat_summary(fun.data=mean_sdl, mult=1, 
                 geom="pointrange", color="red")

# Function to produce summary statistics (mean and +/- sd)
data_summary <- function(x) {
   m <- mean(x)
   ymin <- m-sd(x)
   ymax <- m+sd(x)
   return(c(y=m,ymin=ymin,ymax=ymax))
}

p + stat_summary(fun.data=data_summary, color="blue")

Change point shapes by groups

In the R code below, point shapes are controlled automatically by the variable dose.

You can also set point shapes manually using the function scale_shape_manual()

# Change point shapes by groups
p<-ggplot(ToothGrowth, aes(x=dose, y=len, shape=dose)) + 
    geom_jitter(position=position_jitter(0.2))
p
# Change point shapes manually
p + scale_shape_manual(values=c(1,17,19))

Read more on point shapes : ggplot2 point shapes

Change stripchart colors by groups

In the R code below, point colors of the stripchart are automatically controlled by the levels of dose :

# Use single color
ggplot(ToothGrowth, aes(x=dose, y=len)) + 
    geom_jitter(position=position_jitter(0.2), color="red")
# Change stripchart colors by groups
p<-ggplot(ToothGrowth, aes(x=dose, y=len, color=dose)) +
  geom_jitter(position=position_jitter(0.2))
p

It is also possible to change manually stripchart colors using the functions :

• scale_color_manual() : to use custom colors
• scale_color_brewer() : to use color palettes from RColorBrewer package
• scale_color_grey() : to use grey color palettes

# Use custom color palettes
p+scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))
# Use brewer color palettes
p+scale_color_brewer(palette="Dark2")
# Use grey scale
p + scale_color_grey() + theme_classic()

Read more on ggplot2 colors here : ggplot2 colors

Change the legend position

p + theme(legend.position="top")
p + theme(legend.position="bottom")
p + theme(legend.position="none")# Remove legend

The allowed values for the arguments legend.position are : “left”,“top”, “right”, “bottom”.

Read more on ggplot legends : ggplot2 legend

Change the order of items in the legend

The function scale_x_discrete can be used to change the order of items to “2”, “0.5”, “1” :

p + scale_x_discrete(limits=c("2", "0.5", "1"))

Stripchart with multiple groups

# Change stripchart colors by groups
ggplot(ToothGrowth, aes(x=dose, y=len, color=supp)) +
  geom_jitter(position=position_jitter(0.2))
# Change the position : interval between stripchart of the same group
p<-ggplot(ToothGrowth, aes(x=dose, y=len, color=supp, shape=supp)) +
  geom_jitter(position=position_dodge(0.8))
p

Change stripchart colors and add box plots :

# Change colors
p+scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))
# Add box plots
ggplot(ToothGrowth, aes(x=dose, y=len, color=supp)) +
  geom_boxplot(color="black")+
  geom_jitter(position=position_jitter(0.2))
# Change the position
ggplot(ToothGrowth, aes(x=dose, y=len, color=supp)) +
  geom_boxplot(position=position_dodge(0.8))+
  geom_jitter(position=position_dodge(0.8))

Customized stripcharts

# Basic stripchart
ggplot(ToothGrowth, aes(x=dose, y=len)) + 
  geom_boxplot()+
  geom_jitter(position=position_jitter(0.2))+
  labs(title="Plot of length  by dose",x="Dose (mg)", y = "Length")+
  theme_classic()
# Change color/shape by groups
p <- ggplot(ToothGrowth, aes(x=dose, y=len, color=dose, shape=dose)) + 
  geom_jitter(position=position_jitter(0.2))+
  labs(title="Plot of length  by dose",x="Dose (mg)", y = "Length")
p + theme_classic()

Change colors manually :

# Continuous colors
p + scale_color_brewer(palette="Blues") + theme_classic()
# Discrete colors
p + scale_color_brewer(palette="Dark2") + theme_minimal()
# Gradient colors
p + scale_color_brewer(palette="RdBu")

Read more on ggplot2 colors here : ggplot2 colors

Infos

This analysis has been performed using R software (ver. 3.1.2) and ggplot2 (ver. 1.0.0)

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