nucleotideFrequency {Biostrings} | R Documentation

## Calculate the frequency of oligonucleotides in a DNA or RNA sequence (and other related functions)

### Description

Given a DNA or RNA sequence (or a set of DNA or RNA sequences), the `oligonucleotideFrequency` function computes the frequency of all possible oligonucleotides of a given length (called the "width" in this particular context) in a sliding window that is shifted `step` nucleotides at a time.

The `dinucleotideFrequency` and `trinucleotideFrequency` functions are convenient wrappers for calling `oligonucleotideFrequency` with `width=2` and `width=3`, respectively.

The `nucleotideFrequencyAt` function computes the frequency of the short sequences formed by extracting the nucleotides found at some fixed positions from each sequence of a set of DNA or RNA sequences.

In this man page we call "DNA input" (or "RNA input") an XString, XStringSet, XStringViews or MaskedXString object of base type DNA (or RNA).

### Usage

    oligonucleotideFrequency(x, width, step=1,
                             as.prob=FALSE, as.array=FALSE,
                             fast.moving.side="right", with.labels=TRUE, ...)

    ## S4 method for signature 'XStringSet'
    oligonucleotideFrequency(x, width, step=1,
                             as.prob=FALSE, as.array=FALSE,
                             fast.moving.side="right", with.labels=TRUE,
                             simplify.as="matrix")

    dinucleotideFrequency(x, step=1,
                          as.prob=FALSE, as.matrix=FALSE,
                          fast.moving.side="right", with.labels=TRUE, ...)

    trinucleotideFrequency(x, step=1,
                           as.prob=FALSE, as.array=FALSE,
                           fast.moving.side="right", with.labels=TRUE, ...)

    nucleotideFrequencyAt(x, at,
                          as.prob=FALSE, as.array=TRUE,
                          fast.moving.side="right", with.labels=TRUE, ...)

    ## Some related functions:
    oligonucleotideTransitions(x, left=1, right=1, as.prob=FALSE)

    mkAllStrings(alphabet, width, fast.moving.side="right")

### Arguments

`x` | Any DNA or RNA input for the `*Frequency` and `oligonucleotideTransitions` functions. An XStringSet or XStringViews object of base type DNA or RNA for `nucleotideFrequencyAt`.
`width` | The number of nucleotides per oligonucleotide for `oligonucleotideFrequency`. The number of letters per string for `mkAllStrings`.
`step` | How many nucleotides should the window be shifted before counting the next oligonucleotide (i.e. the sliding window step; default 1). If `step` is smaller than `width`, oligonucleotides will overlap; if the two arguments are equal, adjacent oligonucleotides will be counted (an efficient way to count codons in an ORF); and if `step` is larger than `width`, nucleotides will be sampled `step` nucleotides apart.
`at` | An integer vector containing the positions to look at in each element of `x`.
`as.prob` | If `TRUE` then probabilities are reported, otherwise counts (the default).
`as.array,as.matrix` | Controls the "shape" of the returned object. If `TRUE` (the default for `nucleotideFrequencyAt`) then it's a numeric matrix (or array), otherwise it's just a "flat" numeric vector i.e. a vector with no dim attribute (the default for the `*Frequency` functions).
`fast.moving.side` | Which side of the strings should move fastest? Note that, when `as.array` is TRUE, then the supplied value is ignored and the effective value is `"left"`.
`with.labels` | If `TRUE` then the returned object is named.
`...` | Further arguments to be passed to or from other methods.
`simplify.as` | Together with the `as.array` and `as.matrix` arguments, controls the "shape" of the returned object when the input `x` is an XStringSet or XStringViews object. Supported `simplify.as` values are `"matrix"` (the default), `"list"` and `"collapsed"`. If `simplify.as` is `"matrix"`, the returned object is a matrix with `length(x)` rows where the `i`-th row contains the frequencies for `x[[i]]`. If `simplify.as` is `"list"`, the returned object is a list of the same length as `length(x)` where the `i`-th element contains the frequencies for `x[[i]]`. If `simplify.as` is `"collapsed"`, then the the frequencies are computed for the entire object `x` as a whole (i.e. frequencies cumulated across all sequences in `x`).
`left, right` | The number of nucleotides per oligonucleotide for the rows and columns respectively in the transition matrix created by `oligonucleotideTransitions`.
`alphabet` | The alphabet to use to make the strings.

### Value

If `x` is an XString or MaskedXString object, the `*Frequency` functions return a numeric vector of length `4^width`. If `as.array` (or `as.matrix`) is `TRUE`, then this vector is formatted as an array (or matrix). If `x` is an XStringSet or XStringViews object, the returned object has the shape specified by the `simplify.as` argument.

### Author(s)

H. Pagès and P. Aboyoun; K. Vlahovicek for the `step` argument

### See Also

`alphabetFrequency`, `alphabet`, `hasLetterAt`, XString-class, XStringSet-class, XStringViews-class, MaskedXString-class, `GENETIC_CODE`, `AMINO_ACID_CODE`, `reverseComplement`, `rev`

### Examples

    ## ---------------------------------------------------------------------
    ## A. BASIC *Frequency() EXAMPLES
    ## ---------------------------------------------------------------------
    data(yeastSEQCHR1)
    yeast1 <- DNAString(yeastSEQCHR1)

    dinucleotideFrequency(yeast1)
    trinucleotideFrequency(yeast1)
    oligonucleotideFrequency(yeast1, 4)

    ## Get the counts of tetranucleotides overlapping by one nucleotide:
    oligonucleotideFrequency(yeast1, 4, step=3)

    ## Get the counts of adjacent tetranucleotides, starting from the first
    ## nucleotide:
    oligonucleotideFrequency(yeast1, 4, step=4)

    ## Subset the sequence to change the starting nucleotide (here we start
    ## counting from third nucleotide):
    yeast2 <- subseq(yeast1, start=3)
    oligonucleotideFrequency(yeast2, 4, step=4)

    ## Get the less and most represented 6-mers:
    f6 <- oligonucleotideFrequency(yeast1, 6)
    f6[f6 == min(f6)]
    f6[f6 == max(f6)]

    ## Get the result as an array:
    tri <- trinucleotideFrequency(yeast1, as.array=TRUE)
    tri["A", "A", "C"] # == trinucleotideFrequency(yeast1)["AAC"]
    tri["T", , ] # frequencies of trinucleotides starting with a "T"

    ## With input made of multiple sequences:
    library(drosophila2probe)
    probes <- DNAStringSet(drosophila2probe)
    dfmat <- dinucleotideFrequency(probes)  # a big matrix
    dinucleotideFrequency(probes, simplify.as="collapsed")
    dinucleotideFrequency(probes, simplify.as="collapsed", as.matrix=TRUE)

    ## ---------------------------------------------------------------------
    ## B. OBSERVED DINUCLEOTIDE FREQUENCY VERSUS EXPECTED DINUCLEOTIDE
    ##    FREQUENCY
    ## ---------------------------------------------------------------------
    ## The expected frequency of dinucleotide "ab" based on the frequencies
    ## of its individual letters "a" and "b" is:
    ##    exp_Fab = Fa * Fb / N if the 2 letters are different (e.g. CG)
    ##    exp_Faa = Fa * (Fa-1) / N if the 2 letters are the same (e.g. TT)
    ## where Fa and Fb are the frequencies of "a" and "b" (respectively) and
    ## N the length of the sequence.

    ## Here is a simple function that implements the above formula for a
    ## DNAString object 'x'. The expected frequencies are returned in a 4x4
    ## matrix where the rownames and colnames correspond to the 1st and 2nd
    ## base in the dinucleotide:
    expectedDinucleotideFrequency <- function(x)
    {
        # Individual base frequencies.
        bf <- alphabetFrequency(x, baseOnly=TRUE)[DNA_BASES]
        (as.matrix(bf) %*% t(bf) - diag(bf)) / length(x)
    }

    ## On Celegans chrI:
    library(BSgenome.Celegans.UCSC.ce2)
    chrI <- Celegans$chrI
    obs_df <- dinucleotideFrequency(chrI, as.matrix=TRUE)
    obs_df  # CG has the lowest frequency
    exp_df <- expectedDinucleotideFrequency(chrI)
    ## A sanity check:
    stopifnot(as.integer(sum(exp_df)) == sum(obs_df))

    ## Ratio of observed frequency to expected frequency:
    obs_df / exp_df  # TA has the lowest ratio, not CG!

    ## ---------------------------------------------------------------------
    ## C. nucleotideFrequencyAt()
    ## ---------------------------------------------------------------------
    nucleotideFrequencyAt(probes, 13)
    nucleotideFrequencyAt(probes, c(13, 20))
    nucleotideFrequencyAt(probes, c(13, 20), as.array=FALSE)

    ## nucleotideFrequencyAt() can be used to answer questions like: "how
    ## many probes in the drosophila2 chip have T, G, T, A at position
    ## 2, 4, 13 and 20, respectively?"
    nucleotideFrequencyAt(probes, c(2, 4, 13, 20))["T", "G", "T", "A"]
    ## or "what's the probability to have an A at position 25 if there is
    ## one at position 13?"
    nf <- nucleotideFrequencyAt(probes, c(13, 25))
    sum(nf["A", "A"]) / sum(nf["A", ])
    ## Probabilities to have other bases at position 25 if there is an A
    ## at position 13:
    sum(nf["A", "C"]) / sum(nf["A", ])  # C
    sum(nf["A", "G"]) / sum(nf["A", ])  # G
    sum(nf["A", "T"]) / sum(nf["A", ])  # T

    ## See ?hasLetterAt for another way to get those results.

    ## ---------------------------------------------------------------------
    ## D. oligonucleotideTransitions()
    ## ---------------------------------------------------------------------
    ## Get nucleotide transition matrices for yeast1
    oligonucleotideTransitions(yeast1)
    oligonucleotideTransitions(yeast1, 2, as.prob=TRUE)

    ## ---------------------------------------------------------------------
    ## E. ADVANCED *Frequency() EXAMPLES
    ## ---------------------------------------------------------------------
    ## Note that when dropping the dimensions of the 'tri' array, elements
    ## in the resulting vector are ordered as if they were obtained with
    ## 'fast.moving.side="left"':
    triL <- trinucleotideFrequency(yeast1, fast.moving.side="left")
    all(as.vector(tri) == triL) # TRUE

    ## Convert the trinucleotide frequency into the amino acid frequency
    ## based on translation:
    tri1 <- trinucleotideFrequency(yeast1)
    names(tri1) <- GENETIC_CODE[names(tri1)]
    sapply(split(tri1, names(tri1)), sum) # 12512 occurrences of the stop codon

    ## When the returned vector is very long (e.g. width >= 10), using
    ## 'with.labels=FALSE' can improve performance significantly.
    ## Here for example, the observed speed up is between 25x and 500x:
    f12 <- oligonucleotideFrequency(yeast1, 12, with.labels=FALSE) # very fast!

    ## With the use of 'step', trinucleotideFrequency() is a very fast way to
    ## calculate the codon usage table in an ORF (or a set of ORFs).
    ## Taking the same example as in '?codons':
    file <- system.file("extdata", "someORF.fa", package="Biostrings")
    my_ORFs <- readDNAStringSet(file)
    ## Strip flanking 1000 nucleotides around each ORF and remove first
    ## sequence as it contains an intron:
    my_ORFs <- DNAStringSet(my_ORFs, start=1001, end=-1001)[-1]
    ## Codon usage for each ORF:
    codon_usage <- trinucleotideFrequency(my_ORFs, step=3)
    ## Codon usage across all ORFs:
    global_codon_usage <- trinucleotideFrequency(my_ORFs, step=3,
                                                 simplify.as="collapsed")
    stopifnot(all(colSums(codon_usage) == global_codon_usage))  # sanity check

    ## Some related functions:
    dict1 <- mkAllStrings(LETTERS[1:3], 4)
    dict2 <- mkAllStrings(LETTERS[1:3], 4, fast.moving.side="left")
    stopifnot(identical(reverse(dict1), dict2))

[Package Biostrings version 2.48.0 Index]