Bootstrap motif-summit distances for one set of peaks and one motif

This function performs bootstrapping to estimate the distribution of mean absolute distances between peak summits and motif positions for a given set of peaks and a specified motif.

Usage

bootstrap_distances(
  peaks,
  motif,
  genome_build,
  samples_n = NULL,
  samples_len = NULL,
  out_dir = tempdir(),
  meme_path = NULL,
  verbose = FALSE
)

Arguments

peaks: A GRanges object containing peak ranges.
motif: A universalmotif object.
genome_build: A BSgenome object representing the genome build.
samples_n: An integer specifying the number of bootstrap samples to generate. If NULL, it is set to 70% of the number of peaks.
samples_len: An integer specifying the number of peaks to sample in each bootstrap iteration. If NULL, it is set to 20 peaks.
out_dir: Location to save the 0-order background file. By default, the background file will be written to a temporary directory.
meme_path: path to "meme/bin/" (default: NULL). Will use default search behavior as described in check_meme_install() if unset.
verbose: A logical indicating whether to print verbose messages while running the function. (default = FALSE)

Value

A numeric vector of bootstrapped mean absolute distances between peak summits and motif positions with length equal to samples_n.

Examples

if (memes::meme_is_installed()) {
    peak <- system.file("extdata", "CTCF_ChIP_peaks.narrowPeak",
                package = "MotifPeeker") |>
                read_peak_file() |>
                sample(20)
    motif <- system.file("extdata", "motif_MA1102.3.jaspar",
                package = "MotifPeeker") |> read_motif_file()
                
    if (requireNamespace("BSgenome.Hsapiens.UCSC.hg38")) {
        genome_build <-
            BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38
            
        distances <- bootstrap_distances(
            peak = peak,
            motif = motif,
            genome_build = genome_build,
            samples_n = 2,
            samples_len = NULL,
            verbose = FALSE
        )
        print(distances)
    }
}
#> No matches were detected
#> No matches were detected
#> [1] NA NA