Customizing Legend Colors with ggplot2: A Step-by-Step Guide

Understanding Legend Colors in ggplot2

=====================================================

In this article, we will explore how to define legend colors for a variable in ggplot2. We will begin by creating a dataset and then use ggplot2 to create overlay density plots. However, when trying to assign specific colors to each sample using scale_fill_manual, we encounter an error.

Introduction to ggplot2

ggplot2 is a powerful data visualization library for R that provides a grammar of graphics. It allows users to create complex and customized visualizations with ease. One of the key features of ggplot2 is its ability to handle aesthetics, which include color mapping.

Creating a Dataset

To illustrate this concept, let’s first create a simple dataset:

df <- data.frame(SampleName = c("a","a","a","b","b","b","c","c","c"),
                 Data = c(1,1,2,4,6,7,3,4,9))

Plotting Overlay Density Plots

We can use ggplot2 to create overlay density plots. The first plot will have “a” as the reference sample and “b” as one of the other samples.

ggplot() + 
  geom_density(data=subset(df, SampleName == "a"), 
               aes(x = Data, group=SampleName, fill=SampleName), alpha= 0.6) +
  geom_density(data=subset(df, SampleName == "b"), 
               aes(x = Data, group=SampleName, fill=SampleName), alpha= 0.6) +
  scale_fill_manual(values = c("b" = "red", "a" = "green"))

Looping Over Samples

We can loop over a vector containing all sample names and create overlay plots with “b” as the fixed sample.

Samples <- c("a","b","c")

for(i in 1:length(Samples)){
  print(ggplot() + 
      geom_density(data=subset(df, SampleName == Samples[i]), 
                   aes(x = Data, group=SampleName, fill=SampleName), alpha= 0.6) +
      geom_density(data=subset(df, SampleName == "b"), 
                   aes(x = Data, group=SampleName, fill=SampleName), alpha= 0.6)) +
      scale_fill_manual(values = c("red", "green"))
}

The Problem: Changing Legend Colors

In the above loop, we notice that the samples change colors when “b” is fixed.

for(i in 1:length(Samples)){
  print(ggplot() + 
      geom_density(data=subset(df, SampleName == Samples[i]), 
                   aes(x = Data, group=SampleName, fill=SampleName), alpha= 0.6) +
      geom_density(data=subset(df, SampleName == "b"), 
                   aes(x = Data, group=SampleName, fill=SampleName), alpha= 0.6)) +
      scale_fill_manual(values = c("red", Samples[i] = "green"))
}

The Solution: Using `setNames`

To solve this issue, we can create a named vector using setNames. This allows us to use expressions that need evaluation.

setNames(c('red', 'green'), c('b', Samples[i]))

This makes it easy to assign specific colors to each sample. We can now modify the loop as follows:

for(i in 1:length(Samples)){
  print(ggplot() + 
      geom_density(data=subset(df, SampleName == Samples[i]), 
                   aes(x = Data, group=SampleName, fill=SampleName), alpha= 0.6) +
      geom_density(data=subset(df, SampleName == "b"), 
                   aes(x = Data, group=SampleName, fill=SampleName), alpha= 0.6)) +
      scale_fill_manual(values = setNames(c('red', 'green'), c('b', Samples[i])))
}

Conclusion

In this article, we explored how to define legend colors for a variable in ggplot2. We created a dataset and used ggplot2 to create overlay density plots. However, when trying to assign specific colors to each sample using scale_fill_manual, we encountered an error. We solved this issue by creating a named vector using setNames. This allowed us to use expressions that need evaluation and easily assign specific colors to each sample.