Get Consensus Peak with MSPC.

Get Consensus Peak with MSPC.

GetConsensusPeak(
  peak.file,
  peak.folder = NULL,
  mspc.path = NULL,
  rep.type = c("bio", "tec"),
  stringency.threshold = 1e-08,
  weak.threshold = 1e-04,
  gamma = 1e-08,
  alpha = 0.05,
  min.overlap.num = 1,
  multiple.intersections = c("Lowest", "Highest"),
  parallelism.degree = 1
)

Arguments

peak.file

Peak files (two or more file: get consensus peak; one file: read directly) obtained from peak caller, eg: MACS2 (without header).
peak.folder

The folder contains peak files. Default: NULL.
mspc.path

MSPC path. Default: NULL (conduct automatic detection).
rep.type

Replicate type, chosen from bio (biological) and tec (technical).
stringency.threshold

Set a threshold on p-values, where peaks with p-value lower than this threshold, are considered stringent. Default: 1e-8.
weak.threshold

Set a threshold on p-values, such that peaks with p-value between this and stringency threshold, are considered weak peaks. Default: 1e-4.
gamma

Set the combined stringency threshold. Peaks with combined p-value below this threshold are confirmed. Default: 1e-8.
alpha

Set the threshold for Benjamini-Hochberg multiple testing correction. Default: 0.05.
min.overlap.num

Set the minimum number of overlapping peaks required before MSPC combines their p-value. Default: 1.
multiple.intersections

When multiple peaks from a sample overlap with a given peak, this argument defines which of the peaks to be considered: the one with lowest p-value, or the one with highest p-value? Chosen from Lowest and Highest. Default: Lowest.
parallelism.degree

Set the number of parallel threads MSPC can utilize simultaneously when processing data. Default: 1.

Value

A dataframe contains all consensus peak.

Examples

library(DEbPeak)
peak.file <- system.file("extdata", "debchip_peaks.bed", package = "DEbPeak")
peak.df <- GetConsensusPeak(peak.file = peak.file)