Class 06: R Functions

Aadhya Tripathi (PID: A17878439)

• Background
• A first function
• A second function
• A cool new function

Background

Functions are at the heart of using R. Everything we do involves calling functions (including data input, analysis, results output).

All functions in R have at least 3 things:

1. A name, the thing used to call the function
2. 1+ input arguments, comma separated
3. The body, lines of code between curly brackets { } that do the work of the function

A first function

Write a silly, short function to add some numbers.

add <- function(x) {
  x + 1
}

Let’s try the function!

add(100)

[1] 101

Will this work?

add( c(100,200,300) )

[1] 101 201 301

Modify to be more useful and add more than just 1

add <- function(x, y=1) {
  x + y
}

add(100,10)

[1] 110

Will this work? Yes - if we assign a default value to y

add(100)

[1] 101

N.B. Input arguments can be required OR optional. The optional values have a default fall-back, specified in the function code with an equals sign!

# add(100,200,300)

A second function

All functions in R look like this:

name <- function(arg) { 
  body
}

The sample() function in R takes a random sample of a given size from the elements of a vector.

sample(1:10, size=4)

[1] 2 5 1 7

Q. Return 12 numbers picked randomly from the imput 1:10

sample(1:10, size=12, replace = TRUE)

 [1]  8  8  9  3  2  4  5  2 10  5  2  9

Q. Write the code to generate a random 12 nucleotide long DNA sequence

bases <- c("A", "C", "G", "T")
sample(bases, size=12, replace = TRUE)

 [1] "A" "G" "A" "A" "T" "T" "C" "G" "T" "C" "T" "G"

Q. Write a first version funtion called generate_dna() that generates a user specified length n random DNA sequence.

generate_dna <- function(n=6) {
  bases <- c("A", "C", "G", "T")
  sample(bases, size=n, replace = TRUE)
}

Test:

generate_dna(20)

 [1] "G" "C" "T" "C" "T" "G" "C" "A" "A" "G" "C" "A" "G" "C" "A" "G" "G" "A" "A"
[20] "G"

Q. Modify your function to return a FASTA like sequence (rather than an R vector of individual bases)

generate_dna <- function(n=6) {
  bases <- c("A", "C", "G", "T")
  paste(sample(bases, size=n, replace = TRUE), collapse = "")
}

Test:

generate_dna(10)

[1] "CCGCATCAGT"

Q. Give the user the option to trurn output in FASTA format or standard multi-element vector.

generate_dna <- function(n=6, fasta = TRUE) {
  bases <- c("A", "C", "G", "T")
  seq <- sample(bases, size=n, replace = TRUE)
  
  if(fasta) { 
  seq <- paste(seq, collapse = "")
  }
  
  return(seq)
}

Test:

generate_dna(n=8, fasta=FALSE)

[1] "T" "G" "T" "G" "C" "T" "A" "C"

generate_dna(n=20)

[1] "GGGTATGTATAATCCCCGGT"

A cool new function

Q. Write a fucntion called generate_protein() that generates a user specified length protein sequence in FASTA format.

generate_protein <- function(n=6) {
  aa <- c("A","R","N","D","C",
          "E","Q","G","H","I",
          "L","K","M","F","P",
          "S","T","W","Y","V")
  seq <- sample(aa, size=n, replace = TRUE)
  return (paste(seq, collapse = ""))
}

Test:

generate_protein(12)

[1] "LRQSAFHIFNKS"

Q. Use your new generate_protein() function to generate sequences between length 6 and 12 amino-acids in length. Check if any of these are unique in nature (i.e. found in the NR database at NCBI).

for(i in 6:12) {
  cat(">seq", i, sep="", "\n")
  cat(generate_protein(i), "\n")
}

>seq6
VVREHP 
>seq7
MVHLQTG 
>seq8
PMPTGQYY 
>seq9
NGPEIMRNE 
>seq10
VCDFVDDDGF 
>seq11
YRPLDVCGPDN 
>seq12
QIKILPDDKMAG