gcapcPeaks: GC Effects Aware Peak Calling
In gcapc: GC Aware Peak Caller

Description Usage Arguments Value Examples

View source: R/gcapcPeaks.r

This function calls ChIP-seq peaks using potential GC effects information. Enrichment scores are calculated on sliding windows of prefiltered large regions, with GC effects considered. Permutation analysis is used to determine significant binding peaks.

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gcapcPeaks(coverage, gcbias, bdwidth, flank = NULL, prefilter = 4L,
  permute = 5L, pv = 0.05, plot = FALSE, genome = "hg19",
  gctype = c("ladder", "tricube"))

`coverage`	A list object returned by function `read5endCoverage`.
`gcbias`	A list object returned by function `gcEffects`.
`bdwidth`	A non-negative integer vector with two elements specifying ChIP-seq binding width and peak detection half window size. Usually generated by function `bindWidth`. A bad estimation of bdwidth results no meaning of downstream analysis. The values need to be the same as it is when calculating `gcbias`.
`flank`	A non-negative integer specifying the flanking width of ChIP-seq binding. This parameter provides the flexibility that reads appear in flankings by decreased probabilities as increased distance from binding region. This paramter helps to define effective GC content calculation. Default is NULL, which means this paramater will be calculated from `bdwidth`. However, if customized numbers provided, there won't be recalucation for this parameter; instead, the 2nd elements of `bdwidth` will be recalculated based on `flank`. The value needs to be the same as it is when calculating `gcbias`.
`prefilter`	A non-negative integer specifying the minimum of reads to qualify a potential binding region. Regions with total of reads from forward and reverse strands larger or equivalent to `prefilter` are selected for downstream analysis. Default is 4.
`permute`	A non-negative integer specifying times of permutation to be performed. Default is 5. When whole large genome is used, such as human genome, 5 times of permutation could be enough.
`pv`	A numeric specifying p-value cutoff for significant binding peaks. Default is 0.05.
`plot`	A logical vector which, when TRUE (default), returns density plots of real and permutation enrichment scores.
`genome`	A BSgenome object containing the sequences of the reference genome that was used to align the reads, or the name of this reference genome specified in a way that is accepted by the `getBSgenome` function defined in the BSgenome software package. In that case the corresponding BSgenome data package needs to be already installed (see `?getBSgenome` in the BSgenome package for the details). The value needs to be the same as it is when calculating `gcbias`.
`gctype`	A character vector specifying choice of method to calculate effective GC content. Default `ladder` is based on uniformed fragment distribution. A more smoother method based on tricube assumption is also allowed. However, tricube should be not used if estimated peak half size is 3 times or more larger than estimated bind width. The value needs to be the same as it is when calculating `gcbias`.

A GRanges of peaks with meta columns:

`es`	Estimated enrichment score.
`pv`	p-value.

bam <- system.file("extdata", "chipseq.bam", package="gcapc")
cov <- read5endCoverage(bam)
bdw <- bindWidth(cov)
gcb <- gcEffects(cov, bdw, sampling = c(0.15,1))
gcapcPeaks(cov, gcb, bdw)