callBindingSites-methods {ChIPseqR} | R Documentation

## Predict protein binding sites from high-throughput sequencing data

### Description

Methods for function `callBindingSites` in Package ‘ChIPseqR’. These methods are used to identify protein binding sites from ChIP-seq data.

### Usage

    ## S4 method for signature 'ANY'
    callBindingSites(data, chrLen, plot=TRUE, verbose=TRUE, ..., plotTo)
    ## S4 method for signature 'character'
    callBindingSites(data, type, minQual=70, ...)
    ## S4 method for signature 'matrix'
    callBindingSites(data, chrName="chr", ...)
    ## S4 method for signature 'ReadCounts'
    callBindingSites(data, bind, support, background, bgCutoff=0.9, supCutoff=0.9,
    fdr = 0.05, extend=1, tailCut=0.95, piLambda=0.5, adapt=FALSE, corSummary=median, compress = TRUE,
    digits = 16, plot=TRUE, verbose=TRUE, ask=FALSE, plotTo, ...)

### Arguments

`data` | Either an object containing information about mapped reads or a list. See below for details.
`bind` | Length of binding region to use (see Details).
`support` | Length of support region to use (see Details).
`background` | Length of background window. If this is missing it will be set to 10*(`bind`+2*`support`).
`chrLen` | Numeric vector indicating the length of all chromosomes. Only needed when `data` is an `AlignedRead` object. `readBfaToc` may be used to supply this information.
`bgCutoff` | Numeric value between 0.5 and 1. This determines how much estimates of the background read density are allowed to vary for adjacent windows. Set to 1 to disable cutoff.
`supCutoff` | Numeric value between 0.5 and 1. This determines how much estimates of the support region read density are allowed to vary for forward and reverse strand. Set to 1 to disable cutoff.
`fdr` | Target false discovery rate.
`extend` | Numeric value indicating how far mapped reads should be extended when calculating read counts.
`type` | Format of alignment file (see `readAligned` forr details).
`minQual` | Minimum alignment quality to use. All reads with lower alignment quality are discarded.
`tailCut` | Truncation point used to exclude outliers when estimating null distribution.
`chrName` | Name to use for the single chromosome.
`piLambda` | If `adapt=TRUE` this parameter is used to estimate the proportion of scores not related to binding sites.
`adapt` | Logical indicating whether an adaptive false discovery rate should be used. If this is `FALSE` (the default) the usual Benjamini-Hochberg procedure is used to control the FDR.
`corSummary` | Function used to summarise cross-correlation across chromosomes. See the Details section on binding and support region.
`compress` | Logical indicating whether the return value should be compressed.
`digits` | Number of decimal places to retain for binding site score for compression.
`plot` | Logical. If `plot=TRUE` (the default) some diagnostic plots are produced during the analysis.
`verbose` | Logical. If `verbose=TRUE` (the default) status messages are printed to indicate progress.
`ask` | Logical. Setting this to `TRUE` causes the system to wait for user input before displaying a new plot. See `devAskNewPage`.
`plotTo` | Character string giving the name of a file that should be used to store plots generated during the analysis. If this is not missing a pdf file with the given name will be created.
`...` | Additional arguments. Most methods pass them on to the `ReadCounts` method.

### Details

The length of binding and support regions can either be given as a single value or as a range of possible values (by providing the minimum and maximum). In the latter case the cross-correlation between read counts on forward and reverse strand will be used to determine a value within that range. Note that this may lead sub-optimal choices of binding and support region length.

### Value

An object of class `BindScore` if `compress = FALSE`, otherwise an object of class `RLEBindScore`

### Methods

data = "ANY"

  Default method to handle all forms of input not explicitly handled by their own method. In particular this will be used for objects of class `AlignedRead` and `data.frame` but it will handle class for which a `strandPileup` method is available.

data = "character"

  Allows to use a file name referring to a file of mapped sequence reads as input.

data = "matrix"

  Uses a matrix of read counts (for a single chromosome) as input.

data = "ReadCounts"

  This methods implements the peak calling algorithm. Other methods will typically reformat their input and pass it on to this method.

### See Also

`simpleNucCall` for an interface with nucleosome specific defaults. This function uses `strandPileup`, `startScore`, `getCutoff` and `pickPeak`. See the help pages of these functions for additional detail on the individual steps involved. See `getBindLen` for details on the estimation of binding and support region length.

### Examples

    set.seed(1)

    ## determine binding site locations
    b <- sample(1:1e6, 5000)

    ## sample read locations
    fwd <- unlist(lapply(b, function(x) sample((x-83):(x-73), 20, replace=TRUE)))
    rev <- unlist(lapply(b, function(x) sample((x+73):(x+83), 20, replace=TRUE)))

    ## add some background noise
    fwd <- c(fwd, sample(1:(1e6-25), 50000))
    rev <- c(rev, sample(25:1e6, 50000))

    ## create data.frame with read positions as input to strandPileup
    reads <- data.frame(chromosome="chr1", position=c(fwd, rev),
    	length=25, strand=factor(rep(c("+", "-"), times=c(150000, 150000))))

    ## create object of class ReadCounts
    readPile <- strandPileup(reads, chrLen=1e6, extend=1, plot=FALSE)

    ## predict binding site locations
    ## the artificial dataset is very small so predictions may not be very reliable
    bindScore <- callBindingSites(readPile, bind=147, support=20, background=2000, plot=FALSE)

[Package ChIPseqR version 1.44.0 Index]