Demo2: Useful R functions for working with strings

It is important to note that all strings in R are stored as vectors. For example both of the below are vectors of strings.

v1 <- c("A", "B", "C", "D", "E")
v2 <- "ABCDE"
v1

## [1] "A" "B" "C" "D" "E"

v2

## [1] "ABCDE"

The first vector v1 has 5 elements (i.e values A to E) and is thus of length 5. The second vector v2 has only one element and is of length 1:

length(v1)

## [1] 5

length(v2)

## [1] 1

To find out how many characters (i.e. letters) are in each element of a vector we can use the nchar() function:

nchar(v1)

## [1] 1 1 1 1 1

nchar(v2)

## [1] 5

Note that the example nchar(v1) here shows that the nchar() function is vectorized - that is, it will operate on every element of our input vector without having to explicitly loop over these elements. This is a really cool feature of R!

The paste() function

A particularly useful function is paste(), which constructs strings by “pasting” together the parts. The paste() function takes any number of arguments and concatenates them together using the separating string specified by the sep argument (which is a space by default). Like many of R’s functions, paste() is vectorized:

paste("chr", c(1:22, "X", "Y"), sep="")

##  [1] "chr1"  "chr2"  "chr3"  "chr4"  "chr5"  "chr6"  "chr7"  "chr8" 
##  [9] "chr9"  "chr10" "chr11" "chr12" "chr13" "chr14" "chr15" "chr16"
## [17] "chr17" "chr18" "chr19" "chr20" "chr21" "chr22" "chrX"  "chrY"

What do you think would happen with the following example?

paste(v1, 1)

## [1] "A 1" "B 1" "C 1" "D 1" "E 1"

How about these examples?

paste(v1, c(1:5))

## [1] "A 1" "B 2" "C 3" "D 4" "E 5"

paste(v1, c(1:3))

## [1] "A 1" "B 2" "C 3" "D 1" "E 2"

In the last example above, paste(v1, c(1:3)) we see recycling in operation - in this case the shorter input vector got “recycled” until it matched the length of the longer input vector to produce our output. This is a feature, not a bug!

Pattern matching and replacement with grep() and sub()

The grep() function, like its UNIX namesake, is useful for finding matches within and between strings. Here are some simple examples:

x <- c("AGCTAG", "ATA", "GATCTGAG", "")
length(x)

## [1] 4

nchar(x)

## [1] 6 3 8 0

grep("AT",x)

## [1] 2 3

grep("AT[CG]",x)

## [1] 3

grep("AT[CG]",x, value=TRUE)

## [1] "GATCTGAG"

Unlike grep(), the related regexpr(pattern, x) function returns where in each element of x it matched pattern. If an element doesn’t match the pattern, regexpr() returns –1. For example:

regexpr("AT[CG]",x)

## [1] -1 -1  2 -1
## attr(,"match.length")
## [1] -1 -1  3 -1
## attr(,"useBytes")
## [1] TRUE

Note from the output here the pattern AT[CG] is not found in first, second and fourth element of the vector x but is found in the third element starting at the second character continuing for 3 characters.

The sub() function is useful for replacement of pattern matched segments of strings. For example:

sub("AT[CG]", "--barry--", x)

## [1] "AGCTAG"         "ATA"            "G--barry--TGAG" ""

If you want to match and replace more than the first occurrence of your pattern you will want to use the related gsub() function.

Extracting values from a string

The final function essential to string processing in R is strsplit(x, split), which splits string x by split. Like R’s other string processing functions, strsplit() supports optional perl and fixed arguments.

For example, if we had a string like gene=LEAFY;locus=2159208;gene_model=AT5G61850.1 and we wished to extract each part, we’d need to split by “;”:

y <- "gene=LEAFY;locus=2159208;gene_model=AT5G61850.1"
strsplit(y, ";")

## [[1]]
## [1] "gene=LEAFY"             "locus=2159208"         
## [3] "gene_model=AT5G61850.1"

Also, like all of R’s other string functions, strsplit() is vectorized, so it can process entire character vectors at once. Because the number of split chunks can vary, strsplit() always returns results in a list.