Introduction to R - ARCHIVED

The apply Function

To obtain mean values for all samples we can use mean on each column individually, but there is also an easier way to go about it. Programming languages typically have a way to allow the execution of a single line of code or several lines of code multiple times, or in a “loop”. By default R is not very good at looping, hence the apply() family of functions are used for this purpose. This family includes several functions, each differing slightly on the inputs or outputs. For example, we can use apply() to execute some task on every element in a vector, every row/column in a dataframe, and so on.

base::apply             Apply Functions Over Array Margins
base::by                Apply a Function to a Data Frame Split by Factors
base::eapply            Apply a Function Over Values in an Environment
base::lapply            Apply a Function over a List or Vector (returns list)
base::sapply            Apply a Function over a List or Vector (returns vector)
base::mapply            Apply a Function to Multiple List or Vector Arguments
base::rapply            Recursively Apply a Function to a List
base::tapply            Apply a Function Over a Ragged Array

We will be using apply in our examples today, but do take a moment on your own to explore the many options that are available. The apply function returns a vector or array or list of values obtained by applying a function to margins of an array or matrix. We know about vectors/arrays and functions, but what are these “margins”? Margins are referring to either the rows (denoted by 1), the columns (denoted by 2) or both (1:2). By “both”, we mean apply the function to each individual value.

The syntax for the apply function is:

## DO NOT RUN
apply(dataframe/matrix, margin, function_to_apply)

Let’s try this to obtain mean expression values for each sample in our RPKM matrix:

samplemeans <- apply(rpkm_ordered, 2, mean)