BSgenome-utils {BSgenome} | R Documentation

## BSgenome utilities

### Description

Utilities for BSgenome objects.

### Usage

    ## S4 method for signature 'BSgenome'
    vmatchPattern(pattern, subject, max.mismatch=0, min.mismatch=0,
                  with.indels=FALSE, fixed=TRUE, algorithm="auto",
                  exclude="", maskList=logical(0), userMask=IRangesList(),
                  invertUserMask=FALSE)
    ## S4 method for signature 'BSgenome'
    vcountPattern(pattern, subject, max.mismatch=0, min.mismatch=0,
                  with.indels=FALSE, fixed=TRUE, algorithm="auto",
                  exclude="", maskList=logical(0), userMask=IRangesList(),
                  invertUserMask=FALSE)

    ## S4 method for signature 'BSgenome'
    vmatchPDict(pdict, subject, max.mismatch=0, min.mismatch=0,
                fixed=TRUE, algorithm="auto", verbose=FALSE,
                exclude="", maskList=logical(0))
    ## S4 method for signature 'BSgenome'
    vcountPDict(pdict, subject, max.mismatch=0, min.mismatch=0,
                fixed=TRUE, algorithm="auto", collapse=FALSE,
                weight=1L, verbose=FALSE, exclude="", maskList=logical(0))

    ## S4 method for signature 'BSgenome'
    matchPWM(pwm, subject, min.score="80%", exclude="", maskList=logical(0))
    ## S4 method for signature 'BSgenome'
    countPWM(pwm, subject, min.score="80%", exclude="", maskList=logical(0))

### Arguments

`pattern` | A DNAString object containing the pattern sequence.
`subject` | A BSgenome object containing the subject sequences.
`max.mismatch, min.mismatch` | The maximum and minimum number of mismatching letters allowed (see `?`lowlevel-matching`` for the details). If non-zero, an inexact matching algorithm is used.
`with.indels` | If `TRUE` then indels are allowed. In that case, `min.mismatch` must be `0` and `max.mismatch` is interpreted as the maximum "edit distance" allowed between any pattern and any of its matches (see `?`matchPattern`` for the details).
`fixed` | If `FALSE` then IUPAC extended letters are interpreted as ambiguities (see `?`lowlevel-matching`` for the details).
`algorithm` | For `vmatchPattern` and `vcountPattern` one of the following: `"auto"`, `"naive-exact"`, `"naive-inexact"`, `"boyer-moore"`, `"shift-or"`, or `"indels"`. For `vmatchPDict` and `vcountPDict` one of the following: `"auto"`, `"naive-exact"`, `"naive-inexact"`, `"boyer-moore"`, or `"shift-or"`.
`exclude` | A character vector with strings that will be used to filter out chromosomes whose names match these strings.
`maskList` | A named logical vector of maskStates preferred when used with a BSGenome object. When using the bsapply function, the masks will be set to the states in this vector.
`userMask` | An IntegerRangesList, containing a mask to be applied to each chromosome. See `bsapply`.
`invertUserMask` | Whether the `userMask` should be inverted.
`collapse, weight` | ignored arguments.
`pdict` | A PDict or DNAStringSet object containing the pattern sequences.
`verbose` | `TRUE` or `FALSE`.
`pwm` | A numeric matrix with row names A, C, G and T representing a Position Weight Matrix.
`min.score` | The minimum score for counting a match. Can be given as a character string containing a percentage (e.g. `"85%"`) of the highest possible score or as a single number.

### Value

A GRanges object for `vmatchPattern`.

A data.frame object for `vcountPattern` and `countPWM` with three columns: "seqname" (factor), "strand" (factor), and "count" (integer).

A GRanges object for `vmatchPDict` with one metadata column: "index", which represents a mapping to a position in the original pattern dictionary.

A DataFrame object for `vcountPDict` with four columns: "seqname" ('factor' Rle), "strand" ('factor' Rle), "index" (integer) and "count" ('integer' Rle). As with `vmatchPDict` the index column represents a mapping to a position in the original pattern dictionary.

A GRanges object for `matchPWM` with two metadata columns: "score" (numeric), and "string" (DNAStringSet).

### Author(s)

P. Aboyoun

### See Also

`matchPattern`, `matchPDict`, `matchPWM`, `bsapply`

### Examples

    library(BSgenome.Celegans.UCSC.ce2)
    data(HNF4alpha)

    pattern <- consensusString(HNF4alpha)
    vmatchPattern(pattern, Celegans, fixed="subject")
    vcountPattern(pattern, Celegans, fixed="subject")

    pdict <- PDict(HNF4alpha)
    vmatchPDict(pdict, Celegans)
    vcountPDict(pdict, Celegans)

    pwm <- PWM(HNF4alpha)
    matchPWM(pwm, Celegans)
    countPWM(pwm, Celegans)

[Package BSgenome version 1.56.0 Index]