crossCorrByRle: Calculate cross correlation by extending reads

In jrboyd/peakrefine: Peak Refinement Metric Gathering and Evalutation by Motif Enrichment

Description

Calculate cross correlation by extending reads

Usage

crossCorrByRle(bam_file, query_gr, max_dupes = 1,
  fragment_sizes = 50:300, read_length = NULL, include_plots = TRUE)

Arguments

bam_file	character. Path to .bam file, must have index at .bam.bai.
query_gr	GRanges. Regions to calculate cross correlation for.
max_dupes	integer. Duplicate reads above this value will be removed.
fragment_sizes	integer. fragment size range to search for maximum correlation.
read_length	integer. Any values outside fragment_range that must be searched. If not supplied will be determined from bam_file. Set as NA to disable this behavior.
include_plots	logical. Should plots be included in output?

Value

named list of results

Examples

bam_file = system.file("extdata", "MCF10A_CTCF.random5.bam", package = "peakrefine")
np = system.file("extdata", "MCF10A_CTCF.random5.narrowPeak", package = "peakrefine")
query_gr = rtracklayer::import(np, format = "narrowPeak")
crossCorrByExtension(bam_file, query_gr[1:2], fragment_range = 50:250,
step = 50, small_step = 10)

jrboyd/peakrefine documentation built on July 30, 2020, 7:13 p.m.