Visualization

Plotting With ggplot2

While it is possible to use the base plotting system in R, we are going to focus on using the ggplot2 library to create plots due to it's widespread use in scientific figure generation and the versitility of the package. The basic formula for creating a plot is as such:

library(ggplot2)

ggplot(data = meta, mapping = aes(x = Day, y = OtuCount)) +    # specify what data you are using and what your x and y columns are
  geom_point()   # what type of plot do you want to make? here we make a scatterplot

While we will go through a few plot types in this topic note, we reccomend you check out the R Graph Gallery for a complete list of possible plots and how to make them using the ggplot2 library.

Themes

You are not just limited to a grey background theme when plotting with ggplot2. A poplular theme used in scientific figures is the dark-on-light theme:

ggplot(data = meta, mapping = aes(x = Day, y = OtuCount)) +
  geom_point()+
  theme_bw()

Tip

For a complete list of themes, visit the Complete ggplot2 Themes page

Scaling

Oftentimes your data will span mulitple magnitudes and this can result in an awkward distribution of data. We can scale either your x or y axes using a log scale to remedy this:

ggplot(data = meta, mapping = aes(x = Day, y = OtuCount)) +
  geom_point()+
  theme_bw()+
  scale_y_log10()

Relationships

When plotting two numeric data columns against one another, it might be useful to have a representation of their relationship. Here we show how to add a best fit line:

ggplot(data = meta, mapping = aes(x = Day, y = OtuCount)) +
  geom_point()+
  theme_bw() +
  scale_y_log10() +
  geom_smooth(method="lm")

Panels and Colors

Panels and colors are an important cue to highlight differences in your data:

ggplot(data = meta, 
       mapping = aes(x = Day, y = OtuCount,color = AntibioticUsage)) +    # color by antibiotic usage
  geom_point()+
  facet_wrap(~AntibioticUsage)+    # create different panels for different types of antibiotic usage
  theme_bw()                   

Modifying Text

To modify your text style you can leverage the theme() function:

ggplot(data = meta, mapping = aes(x = AntibioticUsage,fill = AntibioticUsage)) +
  geom_bar()+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45,hjust = 1)) # angle the text by 45 degrees and move the text down by 1 point

You can also modify the x label, y label, title, and title of the legend:

ggplot(data = meta, mapping = aes(x = AntibioticUsage, y = OtuCount,fill= AntibioticUsage)) +
  geom_boxplot()+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45,hjust = 1)) +
  labs(
    x = "Antibiotic Usage",      # x axis title
    y = "OTU Count",             # y axis title
    title = "Figure 1",          # main title of figure
    color = "Antibiotic Usage"   # title of legend
  )