R Bioinformatics Cookbook

How it works...

Step 1 is brief and loads the dataset and libraries we'll need.

In Step 2, we take advantage of a couple of useful parameters in the plotCounts() and results() functions from DESeq2. The returnData flag in plotCounts() will optionally return a tidy dataframe of count information for a given gene in a given condition, hence allowing us to send the data through ggplot() to make a boxplot for an individual gene. The magrittr %>% operator allows us to send the return value of plotCounts() straight to the first positional argument of ggplot() without saving in an intermediate variable.

In Step 3, we use the results() function from DESeq2 to get the results dataframe, which we pipe to dplyr mutate() in order to add a new column ...