CopywriteRCustomBed: CopywriteRCustomBed: ENhanced COpy number Detection from...

In PeeperLab/CopywriteRCustomBed: Copy number information from ChIP_seq using off-target reads off-target reads

Description

Generates DNA copy number profiles from targeted sequencing data using off-target reads This version of CopywriteR allows for custom bed files with peak regions to be used.

Usage

CopywriteRCustomBed(sample.control, Custom.bed, destination.folder, reference.folder, bp.param,
           capture.regions.file, keep.intermediary.files = FALSE, bpWidth = NULL)

Arguments

sample.control	a data.frame or matrix that contains the locations of sample and control BAM files, respectively, in columns. The file locations in a row represent a sample and its corresponding control, which is used for calling peaks.
Custom.bed	Custom list with peak locations in bed format.
destination.folder	the path to the folder to which output should be written. The path can be either absolute or relative.
reference.folder	the path to the folder with the helper files generated by preCopywriteR(). The helper files include the bin, mappability, GC-content, and blacklist, files in .bed format.
bp.param	a BiocParallelParam instance (see BiocParallel Bioconductor pacakage) that determines the settings used for parallel computing. Please refer to the vignette for more information.
capture.regions.file	optional; the path to the capture regions file, which should be in .bed format. Overlapping bait regions should be reduced into single regions. If included, statistics on the overlap of peaks called by MACS and the capture regions will be provided.
keep.intermediary.files	optional; logical that indicates whether intermediary .bam, .bai and peak regions files should be kept after the analysis is done. Defaults to FALSE.
bpWidth	optional; additional number of basepairs to be added around the peak calls. Defaults 0.

Details

CopywriteR uses off-target sequence reads from targeted sequencing to create copy number profiles. First, it removes non-random off-target reads, and it subsequently calculates the depth of coverage for the bins that are provided in the helper files. It then performs GC-content and mappability corrections, and removes blacklisted regions. plotCNA() generates a DNA copy number profile from the output of the CopywriteR() function. Helper files required for CopywriteR analysis can be created using preCopywriteR().

Value

BamBaiPeaksFiles	a folder with the .bam, .bai and peak regions files that are created during the CopywriteR() run. The folder will only be created when the keep.intermediary.files argument is set to TRUE.
input.Rdata	an R object that contains information for plotCNA().
log2_read_counts.igv	the file that contains the compensated corrected read counts after GC-content and mappability corrections, and after removal of data points in blacklisted regions. Counts are log2-transformed. The file is a tab-separated file formatted to be viewed in the IGV genome browser.
CopywriteR.log	log file of CopywriteR.
qc	a folder with quality control files. The .png files contain the plots and the loesses that are used for GC-content and mappability corrections. The fraction_of-bin .pdf files display the empirical cumulative distribution function for the fraction of bin (the bin size after removal of peak regions expressed as a fraction of the original size).
read_counts.txt	the file that contains the raw and compensated read counts per bin.

Author(s)

Thomas Kuilman ([e-mail])

References

CopywriteR: DNA copy number detection from off-target sequence data. Thomas Kuilman, Arno Velds, Kristel Kemper, Marco Ranzani, Lorenzo Bombardelli, Marlous Hoogstraat, Ekaterina Nevedomskaya, Guotai Xu, Julian de Ruiter, Martijn P. Lolkema, Bauke Ylstra, Jos Jonkers, Sven Rottenberg, Lodewyk F. Wessels, David J. Adams, Daniel S. Peeper, Oscar Krijgsman. Submitted for publication.

Examples

## Not run: 
setwd("/PATH/TO/BAMFILES/")
samples <- list.files(pattern = ".bam$", full.names = TRUE)
## Use the first .bam file as a control for every sample
# controls <- samples[rep(1, length(samples))]
## Use every sample as its own control (i.e., peaks are called on sample itself)
controls <- samples
sample.control <- data.frame(samples, controls)

CopywriteRCustomBed(sample.control = sample.control, Custom.bed = Custom.bed, destination.folder =
        "/PATH/TO/DESTINATIONFOLDER/", reference.folder =
        "/PATH/TO/REFERENCEFOLDER", ncpu = nrow(sample.control),
        capture.regions.file <- "/PATH/TO/CAPTUREREGIONSFILE",bpWidth = 0)

## End(Not run)

PeeperLab/CopywriteRCustomBed documentation built on May 17, 2019, 6:34 p.m.