Package 'breakpointR' reference manual

Title:	Find breakpoints in Strand-seq data
Description:	This package implements functions for finding breakpoints, plotting and export of Strand-seq data.
Authors:	David Porubsky, Ashley Sanders, Aaron Taudt
Maintainer:	David Porubsky <[email protected]>
License:	file LICENSE
Version:	1.23.0
Built:	2024-09-28 03:44:17 UTC
Source:	https://github.com/bioc/breakpointR

Breakpoint detection in Strand-Seq data

Description

This package implements functions for finding breakpoints, plotting and export of Strand-seq data.

Details

The main function of this package is breakpointr and produces several plots and browser files. If you want to have more fine-grained control over the different steps check the vignette How to use breakpointR.

Author(s)

David Porubsky, Ashley Sanders, Aaron Taudt

BreakPoint object

Description

The BreakPoint object is output of the function runBreakpointr and is basically a list with various entries. The class() attribute of this list was set to "BreakPoint". Entries can be accessed with the list operators '[[]]' and '$'.

Value

`fragments`	A `GRanges-class` object with read fragments.
`deltas`	A `GRanges-class` object with deltaWs.
`breaks`	A `GRanges-class` object containing the breakpoint coordinates.
`counts`	A `GRanges-class` object with the regions between breakpoints.
`params`	A vector with parameters that were used to obtain the results.

Main function for the breakpointR package

Description

This function is an easy-to-use wrapper to find breakpoints with runBreakpointr in parallel, write the results to file, plot results and find hotspots.

Usage

breakpointr(
  inputfolder,
  outputfolder,
  configfile = NULL,
  numCPU = 1,
  reuse.existing.files = FALSE,
  windowsize = 1e+06,
  binMethod = "size",
  multi.sizes = NULL,
  pairedEndReads = FALSE,
  pair2frgm = FALSE,
  chromosomes = NULL,
  min.mapq = 10,
  filtAlt = FALSE,
  genoT = "fisher",
  trim = 10,
  peakTh = 0.33,
  zlim = 3.291,
  background = 0.05,
  minReads = 10,
  maskRegions = NULL,
  callHotSpots = FALSE,
  conf = 0.99
)
breakpointr(
  inputfolder,
  outputfolder,
  configfile = NULL,
  numCPU = 1,
  reuse.existing.files = FALSE,
  windowsize = 1e+06,
  binMethod = "size",
  multi.sizes = NULL,
  pairedEndReads = FALSE,
  pair2frgm = FALSE,
  chromosomes = NULL,
  min.mapq = 10,
  filtAlt = FALSE,
  genoT = "fisher",
  trim = 10,
  peakTh = 0.33,
  zlim = 3.291,
  background = 0.05,
  minReads = 10,
  maskRegions = NULL,
  callHotSpots = FALSE,
  conf = 0.99
)

Arguments

`inputfolder`	Folder with BAM files.
`outputfolder`	Folder to output the results. If it does not exist it will be created.
`configfile`	A file specifying the parameters of this function (without `inputfolder`, `outputfolder` and `configfile`). Having the parameters in a file can be handy if many samples with the same parameter settings are to be run. If a `configfile` is specified, it will take priority over the command line parameters.
`numCPU`	The numbers of CPUs that are used. Should not be more than available on your machine.
`reuse.existing.files`	A logical indicating whether or not existing files in `outputfolder` should be reused.
`windowsize`	The window size used to calculate deltaWs, either number of reads or genomic size depending on `binMethod`.
`binMethod`	Method used to calculate optimal number of reads in the window ("size", "reads"). By default `binMethod='size'`.
`multi.sizes`	User defined multiplications of the original window size.
`pairedEndReads`	Set to `TRUE` if you have paired-end reads in your file.
`pair2frgm`	Set to `TRUE` if every paired-end read should be merged into a single fragment.
`chromosomes`	If only a subset of the chromosomes should be binned, specify them here.
`min.mapq`	Minimum mapping quality when importing from BAM files.
`filtAlt`	Set to `TRUE` if you want to filter out alternative alignments defined in 'XA' tag.
`genoT`	A method ('fisher' or 'binom') to genotype regions defined by a set of breakpoints.
`trim`	The amount of outliers in deltaWs removed to calculate the stdev (10 will remove top 10% and bottom 10% of deltaWs).
`peakTh`	The treshold that the peak deltaWs must pass to be considered a breakpoint (e.g. 0.33 is 1/3 of max(deltaW)).
`zlim`	The number of stdev that the deltaW must pass the peakTh (ensures only significantly higher peaks are considered).
`background`	The percent (e.g. 0.05 = 5%) of background reads allowed for WW or CC genotype calls.
`minReads`	The minimal number of reads between two breaks required for genotyping.
`maskRegions`	List of regions to be excluded from the analysis (tab-separated file: chromosomes start end).
`callHotSpots`	Search for regions of high abundance of breakpoints in single cells.
`conf`	Desired confidence interval of localized breakpoints.

Value

NULL

Author(s)

David Porubsky, Aaron Taudt, Ashley Sanders

Examples

## Not run: 
## The following call produces plots and genome browser files for all BAM files in "my-data-folder"
breakpointr(inputfolder="my-data-folder", outputfolder="my-output-folder")
## End(Not run)

## Not run: 
## The following call produces plots and genome browser files for all BAM files in "my-data-folder"
breakpointr(inputfolder="my-data-folder", outputfolder="my-output-folder")
## End(Not run)

Export UCSC browser formated files

Description

Write a bedfile or bedgraph from a breakpointR object for upload on to the UCSC Genome browser.

Usage

breakpointr2UCSC(
  index,
  outputDirectory,
  fragments = NULL,
  deltaWs = NULL,
  breakTrack = NULL,
  confidenceIntervals = NULL,
  breaksGraph = NULL
)
breakpointr2UCSC(
  index,
  outputDirectory,
  fragments = NULL,
  deltaWs = NULL,
  breakTrack = NULL,
  confidenceIntervals = NULL,
  breaksGraph = NULL
)

Arguments

`index`	A character used to name the bedfile(s).
`outputDirectory`	Location to write bedfile(s).
`fragments`	A `GRanges-class` object with strand and mapq metadata, such as that generated by `readBamFileAsGRanges`
`deltaWs`	A `GRanges-class` object with metadata column "deltaW" generated by `deltaWCalculator`.
`breakTrack`	A `GRanges-class` object with metadata "genoT" (e.g. newBreaks) will write a bedtrack with refined breakpoints.
`confidenceIntervals`	A `GRanges-class` object with metadata "genoT" the same length as `breakTrack` (e.g. confint) will write a bedtrack with breakpoints confidence intervals.
`breaksGraph`	A `GRanges-class` object.

Value

NULL

Author(s)

Ashley Sanders, David Porubsky, Aaron Taudt

Examples

## Get an example file
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file 
brkpts <- get(load(exampleFile))
## Write results to BED files
breakpointr2UCSC(index='testfile', outputDirectory=tempdir(), breakTrack=brkpts$breaks)
## Get an example file
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file 
brkpts <- get(load(exampleFile))
## Write results to BED files
breakpointr2UCSC(index='testfile', outputDirectory=tempdir(), breakTrack=brkpts$breaks)

Find breakpoints from deltaWs

Description

Find breakpoints from deltaWs by localizing significant peaks based on z-score calculation.

Usage

breakSeekr(deltaWs, trim = 10, peakTh = 0.33, zlim = 3.291)
breakSeekr(deltaWs, trim = 10, peakTh = 0.33, zlim = 3.291)

Arguments

`deltaWs`	A `GRanges-class` object with metadata column "deltaW" generated by `deltaWCalculator`.
`trim`	The amount of outliers in deltaWs removed to calculate the stdev (10 will remove top 10% and bottom 10% of deltaWs).
`peakTh`	The treshold that the peak deltaWs must pass to be considered a breakpoint (e.g. 0.33 is 1/3 of max(deltaW)).
`zlim`	The number of stdev that the deltaW must pass the peakTh (ensures only significantly higher peaks are considered).

Value

A GRanges-class object containing breakpoint coordinates with various metadata columns.

Author(s)

David Porubsky, Aaron Taudt, Ashley Sanders

Examples

## Get an example file 
exampleFolder <- system.file("extdata", "example_bams", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file
fragments <- readBamFileAsGRanges(exampleFile, pairedEndReads=FALSE, chromosomes='chr22')
## Calculate deltaW values
dw <- deltaWCalculator(fragments)
## Get significant peaks in deltaW values
breaks <- breakSeekr(dw)

## Get an example file 
exampleFolder <- system.file("extdata", "example_bams", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file
fragments <- readBamFileAsGRanges(exampleFile, pairedEndReads=FALSE, chromosomes='chr22')
## Calculate deltaW values
dw <- deltaWCalculator(fragments)
## Get significant peaks in deltaW values
breaks <- breakSeekr(dw)

Collapse consecutive bins with the same ID value

Description

Collapse consecutive bins with the same value defined in 'id.field'.

Usage

collapseBins(gr, id.field = 3)
collapseBins(gr, id.field = 3)

Arguments

`gr`	A `GRanges-class` object.
`id.field`	A number of metadata column to use for region merging.

Value

A GRanges-class object.

Estimate confidence intervals for breakpoints

Description

Estimate confidence intervals for breakpoints by going outwards from the breakpoint read by read, and multiplying the probability that the read doesn't belong to the assigned segment.

Usage

confidenceInterval(breaks, fragments, background = 0.05, conf = 0.99)
confidenceInterval(breaks, fragments, background = 0.05, conf = 0.99)

Arguments

`breaks`	Genotyped breakpoints as outputted from function `GenotypeBreaks`.
`fragments`	Read fragments from function `readBamFileAsGRanges`.
`background`	The percent (e.g. 0.05 = 5%) of background reads allowed for WW or CC genotype calls.
`conf`	Desired confidence interval of localized breakpoints.

Value

A GRanges-class object of breakpoint ranges for a given confidence interval in conf.

Author(s)

Aaron Taudt, David Porubsky

Examples

## Not run:  
## Get an example file 
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file 
breakpoint.objects <- get(load(exampleFile))
## Calculate confidence intervals of genotyped breakpoints
confint <- confidenceInterval(breaks=breakpoint.objects$breaks, fragments=breakpoint.objects$fragments, background=0.02)
## End(Not run)

## Not run:  
## Get an example file 
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file 
breakpoint.objects <- get(load(exampleFile))
## Calculate confidence intervals of genotyped breakpoints
confint <- confidenceInterval(breaks=breakpoint.objects$breaks, fragments=breakpoint.objects$fragments, background=0.02)
## End(Not run)

Estimate confidence intervals for breakpoints

Description

Estimate confidence intervals for breakpoints by going outwards from the breakpoint read by read, and performing a binomial test of getting the observed or a more extreme outcome, given that the reads within the confidence interval belong to the other side of the breakpoint.

Usage

confidenceInterval.binomial(breaks, fragments, background = 0.02, conf = 0.99)
confidenceInterval.binomial(breaks, fragments, background = 0.02, conf = 0.99)

Arguments

`breaks`	Genotyped breakpoints as outputted from function `GenotypeBreaks`.
`fragments`	Read fragments from function `readBamFileAsGRanges`.
`background`	The percent (e.g. 0.05 = 5%) of background reads allowed for WW or CC genotype calls.
`conf`	Desired confidence interval of localized breakpoints.

Value

A GRanges-class object of breakpoint ranges for a given confidence interval in conf.

Author(s)

Aaron Taudt, David Porubsky

Examples

## Not run:  
## Get an example file 
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file 
breakpoint.objects <- get(load(exampleFile))
## Calculate confidence intervals of genotyped breakpoints
confint <- confidenceInterval.binomial(breakpoint.objects$breaks, breakpoint.objects$fragments, background=0.02)
## End(Not run)

## Not run:  
## Get an example file 
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file 
breakpoint.objects <- get(load(exampleFile))
## Calculate confidence intervals of genotyped breakpoints
confint <- confidenceInterval.binomial(breakpoint.objects$breaks, breakpoint.objects$fragments, background=0.02)
## End(Not run)

Create composite Strand-seq file

Description

This function will move through BAM files in a folder, read in each individual file and go through each chromosome, determine if the chromosome is WW or CC based on WCcutoff, reverse complement all reads in the WW file, append to a new composite file for that chromosome, order the composite file of each chromosome based on position.

Usage

createCompositeFile(
  file.list,
  chromosomes = NULL,
  pairedEndReads = TRUE,
  pair2frgm = FALSE,
  min.mapq = 10,
  filtAlt = FALSE,
  WC.cutoff = 0.9,
  genoT = "fisher",
  background = 0.05
)
createCompositeFile(
  file.list,
  chromosomes = NULL,
  pairedEndReads = TRUE,
  pair2frgm = FALSE,
  min.mapq = 10,
  filtAlt = FALSE,
  WC.cutoff = 0.9,
  genoT = "fisher",
  background = 0.05
)

Arguments

`file.list`	A list of BAM files to process.
`chromosomes`	If only a subset of the chromosomes should be binned, specify them here.
`pairedEndReads`	Set to `TRUE` if you have paired-end reads in your file.
`pair2frgm`	Set to `TRUE` if every paired-end read should be merged into a single fragment.
`min.mapq`	Minimum mapping quality when importing from BAM files.
`filtAlt`	Set to `TRUE` if you want to filter out alternative alignments defined in 'XA' tag.
`WC.cutoff`	Percentage of WW or CC reads to consider chromosome being WW or CC
`genoT`	A method ('fisher' or 'binom') to genotype regions defined by a set of breakpoints.
`background`	The percent (e.g. 0.05 = 5%) of background reads allowed for WW or CC genotype calls.

Value

A GRanges-class object.

Author(s)

Ashley Sanders, David Porubsky

Calculate deltaWs

Description

This function will calculate deltaWs from a GRanges-class object with read fragments.

Usage

deltaWCalculator(frags, reads.per.window = 100)
deltaWCalculator(frags, reads.per.window = 100)

Arguments

`frags`	A `GRanges-class` with read fragments (see `readBamFileAsGRanges`).
`reads.per.window`	Number of reads in each dynamic window.

Value

The input frags with additional meta-data columns.

Author(s)

Aaron Taudt

Examples

## Get an example file
exampleFolder <- system.file("extdata", "example_bams", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file
fragments <- readBamFileAsGRanges(exampleFile, pairedEndReads=FALSE, chromosomes='chr22')
## Calculate deltaW values
dw <- deltaWCalculator(fragments)

## Get an example file
exampleFolder <- system.file("extdata", "example_bams", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file
fragments <- readBamFileAsGRanges(exampleFile, pairedEndReads=FALSE, chromosomes='chr22')
## Calculate deltaW values
dw <- deltaWCalculator(fragments)

Calculate deltaWs using various window sizes

Description

This function will calculate deltaWs from a GRanges-class object with read fragments.

Usage

deltaWCalculatorVariousWindows(
  frags,
  reads.per.window = 100,
  multi.sizes = c(2, 4, 6)
)
deltaWCalculatorVariousWindows(
  frags,
  reads.per.window = 100,
  multi.sizes = c(2, 4, 6)
)

Arguments

`frags`	A `GRanges-class` with read fragments (see `readBamFileAsGRanges`).
`reads.per.window`	Number of reads in each dynamic window.
`multi.sizes`	User defined multiplications of the original window size.

Value

The input frags with additional meta-data columns.

Author(s)

David Porubsky

Function to print WC regions after breakpointR analysis

Description

Function to print WC regions after breakpointR analysis

Usage

exportRegions(
  datapath,
  file = NULL,
  collapseInversions = FALSE,
  collapseRegionSize = 5e+06,
  minRegionSize = 5e+06,
  state = "wc"
)
exportRegions(
  datapath,
  file = NULL,
  collapseInversions = FALSE,
  collapseRegionSize = 5e+06,
  minRegionSize = 5e+06,
  state = "wc"
)

Arguments

`datapath`	A path to that
`file`	A filename to print exported regions to.
`collapseInversions`	Set to `TRUE` if you want to collapse putative inverted regions.
`collapseRegionSize`	Upper range of what sized regions should be collapsed.
`minRegionSize`	Minimal size of the region to be reported.
`state`	A genotype of the regions to be exported ('ww', 'cc' or 'wc').

Value

A data.frame object containing all regions with user defined 'state'.

Author(s)

David Porubsky

Examples

## Get an example file
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
## To export regions genotyped as 'wc'
wc.regions <- exportRegions(datapath=exampleFolder, collapseInversions=FALSE, minRegionSize=5000000, state='wc') 
## Get an example file
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
## To export regions genotyped as 'wc'
wc.regions <- exportRegions(datapath=exampleFolder, collapseInversions=FALSE, minRegionSize=5000000, state='wc')

Assign states to any given region using binomial test.

Description

Assign states to any given region using binomial test.

Usage

genotype.binom(wReads, cReads, background = 0.05, minReads = 10, log = FALSE)
genotype.binom(wReads, cReads, background = 0.05, minReads = 10, log = FALSE)

Arguments

`wReads`	Number of Watson reads.
`cReads`	Number of Crick reads.
`background`	The percent (e.g. 0.05 = 5%) of background reads allowed for WW or CC genotype calls.
`minReads`	The minimal number of reads between two breaks required for genotyping.
`log`	Set to `TRUE` if you want to calculate probability in log space.

Value

A list with the $bestFit and $pval.

Author(s)

David Porubsky

Examples

## Get Crick and Watson read counts
## Crick read count
cReads <- 30
## Watson read count
wReads <- 5  
genotype.binom(cReads = cReads, wReads = wReads, background = 0.05, minReads = 10, log = TRUE)

## Get Crick and Watson read counts
## Crick read count
cReads <- 30
## Watson read count
wReads <- 5  
genotype.binom(cReads = cReads, wReads = wReads, background = 0.05, minReads = 10, log = TRUE)

Assign states to any given region using Fisher Exact Test.

Description

Assign states to any given region using Fisher Exact Test.

Usage

genotype.fisher(cReads, wReads, roiReads, background = 0.05, minReads = 10)
genotype.fisher(cReads, wReads, roiReads, background = 0.05, minReads = 10)

Arguments

`cReads`	Number of Crick reads.
`wReads`	Number of Watson reads.
`roiReads`	Total number of Crick and Watson reads.
`background`	The percent (e.g. 0.05 = 5%) of background reads allowed for WW or CC genotype calls.
`minReads`	The minimal number of reads between two breaks required for genotyping.

Value

A list with the $bestFit and $pval.

Author(s)

David Porubsky, Aaron Taudt

Examples

## Get Crick and Watson read counts
## Crick read count
cReads <- 30
## Watson read count
wReads <- 5  
genotype.fisher(cReads = cReads, wReads = wReads, roiReads = cReads + wReads, background = 0.05, minReads = 10)

## Get Crick and Watson read counts
## Crick read count
cReads <- 30
## Watson read count
wReads <- 5  
genotype.fisher(cReads = cReads, wReads = wReads, roiReads = cReads + wReads, background = 0.05, minReads = 10)

Set of functions to genotype regions in between localized breakpoints

Description

Each defined region is given one of the three states ('ww', 'cc' or 'wc') Consecutive regions with the same state are collapsed

Usage

GenotypeBreaks(
  breaks,
  fragments,
  background = 0.05,
  minReads = 10,
  genoT = "fisher"
)
GenotypeBreaks(
  breaks,
  fragments,
  background = 0.05,
  minReads = 10,
  genoT = "fisher"
)

Arguments

`breaks`	A `GRanges-class` object with breakpoint coordinates.
`fragments`	A `GRanges-class` object with read fragments.
`background`	The percent (e.g. 0.05 = 5%) of background reads allowed for WW or CC genotype calls.
`minReads`	The minimal number of reads between two breaks required for genotyping.
`genoT`	A method ('fisher' or 'binom') to genotype regions defined by a set of breakpoints.

Details

Function GenotypeBreaks exports states of each region defined by breakpoints. Function genotype.fisher assigns states to each region based on expected counts of Watson and Crick reads. Function genotype.binom assigns states to each region based on expected counts of Watson and Crick reads.

Value

A GRanges-class object with genotyped breakpoint coordinates.

Functions

GenotypeBreaks(): Genotypes breakpoint defined regions.

Author(s)

David Porubsky, Ashley Sanders, Aaron Taudt

Examples

## Get an example file 
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file 
breakpoint.objects <- get(load(exampleFile))
## Genotype regions between breakpoints
gbreaks <- GenotypeBreaks(breaks=breakpoint.objects$breaks, fragments=breakpoint.objects$fragments)

## Get an example file 
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file 
breakpoint.objects <- get(load(exampleFile))
## Genotype regions between breakpoints
gbreaks <- GenotypeBreaks(breaks=breakpoint.objects$breaks, fragments=breakpoint.objects$fragments)

Find hotspots of genomic events

Description

Find hotspots of genomic events by using kernel density estimation.

Usage

hotspotter(gr.list, bw, pval = 1e-08)
hotspotter(gr.list, bw, pval = 1e-08)

Arguments

`gr.list`	A list or `GRangesList-class` with `GRanges-class` object containing the coordinates of the genomic events.
`bw`	Bandwidth used for kernel density estimation (see `density`).
`pval`	P-value cutoff for hotspots.

Details

The hotspotter uses density to perform a KDE. A p-value is calculated by comparing the density profile of the genomic events with the density profile of a randomly subsampled set of genomic events. Due to this random sampling, the result can vary for each function call, most likely for hotspots whose p-value is close to the specified pval.

Value

A GRanges-class object containing coordinates of hotspots with p-values.

Author(s)

Aaron Taudt

Examples

## Get example BreakPoint objects
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFiles <- list.files(exampleFolder, full.names=TRUE)
breakpoint.objects <- loadFromFiles(exampleFiles)
## Extract breakpoint coordinates
breaks <- lapply(breakpoint.objects, '[[', 'breaks')
## Get hotspot coordinates
hotspots <- hotspotter(gr.list=breaks, bw=1e6)

## Get example BreakPoint objects
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFiles <- list.files(exampleFolder, full.names=TRUE)
breakpoint.objects <- loadFromFiles(exampleFiles)
## Extract breakpoint coordinates
breaks <- lapply(breakpoint.objects, '[[', 'breaks')
## Get hotspot coordinates
hotspots <- hotspotter(gr.list=breaks, bw=1e6)

Insert chromosome for in case it's missing

Description

Add two columns with transformed genomic coordinates to the GRanges-class object. This is useful for making genomewide plots.

Usage

insertchr(gr)
insertchr(gr)

Arguments

`gr`	A `GRanges-class` object.

Value

The input GRanges-class object with an additional metadata column containing chromosome name with 'chr'.

Load breakpointR objects from file

Description

Wrapper to load breakpointR objects from file and check the class of the loaded objects.

Usage

loadFromFiles(files, check.class = c("GRanges", "BreakPoint"))
loadFromFiles(files, check.class = c("GRanges", "BreakPoint"))

Arguments

`files`	A list of `GRanges-class` or `BreakPoint` objects or a vector of files that contain such objects.
`check.class`	Any combination of `c('GRanges', 'BreakPoint')`. If any of the loaded objects does not belong to the specified class, an error is thrown.

Value

A list of GRanges-class or BreakPoint objects.

Examples

## Get some files that you want to load
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFiles <- list.files(exampleFolder, full.names=TRUE)
## Load the processed data                          
breakpoint.objects <- loadFromFiles(exampleFiles)
## Get some files that you want to load
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFiles <- list.files(exampleFolder, full.names=TRUE)
## Load the processed data                          
breakpoint.objects <- loadFromFiles(exampleFiles)

Plotting genome-wide ideograms breakpointR

Description

This function will create genome-wide ideograms from a BreakPoint object.

Usage

plotBreakpoints(files2plot, file = NULL)
plotBreakpoints(files2plot, file = NULL)

Arguments

`files2plot`	A list of files that contains `BreakPoint` objects or a single `BreakPoint` object.
`file`	Name of the file to plot to.

Value

A list with ggplot objects.

Author(s)

David Porubsky, Aaron Taudt, Ashley Sanders

Examples

## Get an example file
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Plot the file
plotBreakpoints(files2plot=exampleFile)
## Get an example file
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Plot the file
plotBreakpoints(files2plot=exampleFile)

Plotting chromosome specific ideograms breakpointR

Description

This function will create chromsome specific enome-wide ideograms from a BreakPoint object.

Usage

plotBreakpointsPerChr(files2plot, plotspath = NULL, chromosomes = NULL)
plotBreakpointsPerChr(files2plot, plotspath = NULL, chromosomes = NULL)

Arguments

`files2plot`	A list of files that contains `BreakPoint` objects or a single `BreakPoint` object.
`plotspath`	Directory to store plots.
`chromosomes`	Set specific chromosome(s) to be plotted.

Value

A list with ggplot objects.

Author(s)

David Porubsky

Examples

## Get an example file
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFiles <- list.files(exampleFolder, full.names=TRUE)
## Plot results
plotBreakpointsPerChr(exampleFiles, chromosomes='chr7')

## Get an example file
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFiles <- list.files(exampleFolder, full.names=TRUE)
## Plot results
plotBreakpointsPerChr(exampleFiles, chromosomes='chr7')

Genome wide heatmap of template inheritance states

Description

Plot a genome-wide heatmap of template inheritance states from a BreakPoint object.

Usage

plotHeatmap(files2plot, file = NULL, hotspots = NULL)
plotHeatmap(files2plot, file = NULL, hotspots = NULL)

Arguments

`files2plot`	A list of files that contains `BreakPoint` objects or a single `BreakPoint` object.
`file`	Name of the file to plot to.
`hotspots`	A `GRanges-class` object with locations of breakpoint hotspots.

Value

A ggplot object.

Author(s)

David Porubsky, Aaron Taudt, Ashley Sanders

Examples

## Get example BreakPoint objects to plot
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFiles <- list.files(exampleFolder, full.names=TRUE)
breakpoint.objects <- loadFromFiles(exampleFiles)
## Plot the heatmap
plotHeatmap(breakpoint.objects)

## Get example BreakPoint objects to plot
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFiles <- list.files(exampleFolder, full.names=TRUE)
breakpoint.objects <- loadFromFiles(exampleFiles)
## Plot the heatmap
plotHeatmap(breakpoint.objects)

Generates a bedfile from an input GRanges file

Description

Write a bedfile from Breakpoint.R files for upload on to UCSC Genome browser

Usage

ranges2UCSC(gr, outputDirectory = ".", index = "bedFile", colorRGB = "0,0,0")
ranges2UCSC(gr, outputDirectory = ".", index = "bedFile", colorRGB = "0,0,0")

Arguments

`gr`	A `GRanges-class` object with genomic ranges to be exported into UCSC format.
`outputDirectory`	Location to write bedfile(s).
`index`	A character used to name the bedfile(s).
`colorRGB`	An RGB color to be used for submitted ranges.

Value

NULL

Author(s)

David Porubsky

Examples

## Get an example file
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file 
counts <- get(load(exampleFile))[['counts']]
## Export 'wc' states into a UCSC formated file
ranges2UCSC(gr=counts[counts$states == 'wc'], index='testfile', outputDirectory=tempdir())
## Get an example file
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file 
counts <- get(load(exampleFile))[['counts']]
## Export 'wc' states into a UCSC formated file
ranges2UCSC(gr=counts[counts$states == 'wc'], index='testfile', outputDirectory=tempdir())

Import BAM file into GRanges

Description

Import aligned reads from a BAM file into a GRanges-class object.

Usage

readBamFileAsGRanges(
  file,
  bamindex = file,
  chromosomes = NULL,
  pairedEndReads = FALSE,
  min.mapq = 10,
  remove.duplicate.reads = TRUE,
  pair2frgm = FALSE,
  filtAlt = FALSE
)
readBamFileAsGRanges(
  file,
  bamindex = file,
  chromosomes = NULL,
  pairedEndReads = FALSE,
  min.mapq = 10,
  remove.duplicate.reads = TRUE,
  pair2frgm = FALSE,
  filtAlt = FALSE
)

Arguments

`file`	Bamfile with aligned reads.
`bamindex`	Bam-index file with or without the .bai ending. If this file does not exist it will be created and a warning is issued.
`chromosomes`	If only a subset of the chromosomes should be binned, specify them here.
`pairedEndReads`	Set to `TRUE` if you have paired-end reads in your file.
`min.mapq`	Minimum mapping quality when importing from BAM files.
`remove.duplicate.reads`	A logical indicating whether or not duplicate reads should be kept.
`pair2frgm`	Set to `TRUE` if every paired-end read should be merged into a single fragment.
`filtAlt`	Set to `TRUE` if you want to filter out alternative alignments defined in 'XA' tag.

Value

A GRanges-class object.

Author(s)

David Porubsky, Aaron Taudt, Ashley Sanders

Examples

## Get an example file 
exampleFolder <- system.file("extdata", "example_bams", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file
fragments <- readBamFileAsGRanges(exampleFile, pairedEndReads=FALSE, chromosomes='chr22')
## Get an example file 
exampleFolder <- system.file("extdata", "example_bams", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Load the file
fragments <- readBamFileAsGRanges(exampleFile, pairedEndReads=FALSE, chromosomes='chr22')

Read breakpointR configuration file

Description

Read an breakpointR configuration file into a list structure. The configuration file has to be specified in INI format. R expressions can be used and will be evaluated.

Usage

readConfig(configfile)
readConfig(configfile)

Arguments

configfile

Path to the configuration file

Value

A list with one entry for each element in configfile.

Author(s)

Aaron Taudt

Process double SCE chromosomes: with internal WC region.

Description

This function will take from a double SCE chromosome only WW or CC region (Longer region is taken).

Usage

removeDoubleSCEs(gr, collapseWidth = 5e+06)
removeDoubleSCEs(gr, collapseWidth = 5e+06)

Arguments

`gr`	A `GRanges-class` object.
`collapseWidth`	A segment size to be collapsed with neighbouring segments.

Value

The input GRanges-class object with only WW or CC region retained.

Remove large spikes in short reads coverage

Description

This function takes a GRanges-class object of aligned short reads and removes pockets of reads that are stacked on top of each other based on the maximum number of reads allowed to pileup in 'max.pileup' parameter.

Usage

removeReadPileupSpikes(gr = NULL, max.pileup = 30)
removeReadPileupSpikes(gr = NULL, max.pileup = 30)

Arguments

`gr`	A `GRanges-class` object.
`max.pileup`	A maximum number of reads overlapping each other to be kept.

Value

A GRanges-class object.

Author(s)

David Porubsky

Examples

## Get some files that you want to load
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
infile <- list.files(exampleFolder, full.names=TRUE)[1]
## Read in the reads
breakP.obj <- get(load(infile))
frags <- breakP.obj$fragments 
## Remove read spikes
frags <- removeReadPileupSpikes(gr=frags)

## Get some files that you want to load
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
infile <- list.files(exampleFolder, full.names=TRUE)[1]
## Read in the reads
breakP.obj <- get(load(infile))
frags <- breakP.obj$fragments 
## Remove read spikes
frags <- removeReadPileupSpikes(gr=frags)

Find breakpoints in Strand-seq data

Description

Find breakpoints in Strand-seq data. See section Details on how breakpoints are located.

Usage

runBreakpointr(
  bamfile,
  ID = basename(bamfile),
  pairedEndReads = TRUE,
  chromosomes = NULL,
  windowsize = 1e+06,
  binMethod = "size",
  multi.sizes = NULL,
  trim = 10,
  peakTh = 0.33,
  zlim = 3.291,
  background = 0.05,
  min.mapq = 10,
  pair2frgm = FALSE,
  filtAlt = FALSE,
  genoT = "fisher",
  minReads = 20,
  maskRegions = NULL,
  conf = 0.99
)
runBreakpointr(
  bamfile,
  ID = basename(bamfile),
  pairedEndReads = TRUE,
  chromosomes = NULL,
  windowsize = 1e+06,
  binMethod = "size",
  multi.sizes = NULL,
  trim = 10,
  peakTh = 0.33,
  zlim = 3.291,
  background = 0.05,
  min.mapq = 10,
  pair2frgm = FALSE,
  filtAlt = FALSE,
  genoT = "fisher",
  minReads = 20,
  maskRegions = NULL,
  conf = 0.99
)

Arguments

`bamfile`	A file with aligned reads in BAM format.
`ID`	A character string that will serve as identifier in downstream functions.
`pairedEndReads`	Set to `TRUE` if you have paired-end reads in your file.
`chromosomes`	If only a subset of the chromosomes should be binned, specify them here.
`windowsize`	The window size used to calculate deltaWs, either number of reads or genomic size depending on `binMethod`.
`binMethod`	Method used to calculate optimal number of reads in the window ("size", "reads"). By default `binMethod='size'`.
`multi.sizes`	User defined multiplications of the original window size.
`trim`	The amount of outliers in deltaWs removed to calculate the stdev (10 will remove top 10% and bottom 10% of deltaWs).
`peakTh`	The treshold that the peak deltaWs must pass to be considered a breakpoint (e.g. 0.33 is 1/3 of max(deltaW)).
`zlim`	The number of stdev that the deltaW must pass the peakTh (ensures only significantly higher peaks are considered).
`background`	The percent (e.g. 0.05 = 5%) of background reads allowed for WW or CC genotype calls.
`min.mapq`	Minimum mapping quality when importing from BAM files.
`pair2frgm`	Set to `TRUE` if every paired-end read should be merged into a single fragment.
`filtAlt`	Set to `TRUE` if you want to filter out alternative alignments defined in 'XA' tag.
`genoT`	A method ('fisher' or 'binom') to genotype regions defined by a set of breakpoints.
`minReads`	The minimal number of reads between two breaks required for genotyping.
`maskRegions`	List of regions to be excluded from the analysis in `GRanges-class` object.
`conf`	Desired confidence interval of localized breakpoints.

Details

Breakpoints are located in the following way:

calculate deltaWs chromosome-by-chromsome
localize breaks that pass zlim above the threshold
genotype both sides of breaks to confirm whether strand state changes
write a file of _reads, _deltaWs and _breaks in a chr fold -> can upload on to UCSC Genome browser
write a file for each index with all chromosomes included -> can upload on to UCSC Genome browser

Value

A BreakPoint object.

Author(s)

David Porubsky, Ashley Sanders, Aaron Taudt

Examples

## Get an example file
exampleFolder <- system.file("extdata", "example_bams", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Run breakpointR
brkpts <- runBreakpointr(exampleFile, chromosomes='chr22', pairedEndReads=FALSE)

## Get an example file
exampleFolder <- system.file("extdata", "example_bams", package="breakpointRdata")
exampleFile <- list.files(exampleFolder, full.names=TRUE)[1]
## Run breakpointR
brkpts <- runBreakpointr(exampleFile, chromosomes='chr22', pairedEndReads=FALSE)

Compile breakpoint summary table

Description

This function will calculate deltaWs from a GRanges-class object with read fragments.

Usage

summarizeBreaks(breakpoints)
summarizeBreaks(breakpoints)

Arguments

breakpoints

A list containing breakpoints stored in GRanges-class object.

Value

A data.frame of compiled breakpoints together with confidence intervals.

Author(s)

David Porubsky

Examples

## Get some files that you want to load
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
file <- list.files(exampleFolder, full.names=TRUE)[1]
breakpoints <- get(load(file))[c('breaks', 'confint')]
summarizeBreaks(breakpoints)
## Get some files that you want to load
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
file <- list.files(exampleFolder, full.names=TRUE)[1]
breakpoints <- get(load(file))[c('breaks', 'confint')]
summarizeBreaks(breakpoints)

Synchronize Strand-seq read directionality

Description

This function aims to synchronize strand directionality of reads that fall into WW and CC regions.

Usage

synchronizeReadDir(files2sync, collapseWidth = 5e+06)
synchronizeReadDir(files2sync, collapseWidth = 5e+06)

Arguments

`files2sync`	A list of files that contains `BreakPoint` objects.
`collapseWidth`	A segment size to be collapsed with neighbouring segments.

Value

A GRanges-class object that reads synchronized by directionality.

Author(s)

David Porubsky

Examples

## Get some files that you want to load
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
files2sync <- list.files(exampleFolder, full.names=TRUE)[1]
synchronizeReadDir(files2sync=files2sync)

## Get some files that you want to load
exampleFolder <- system.file("extdata", "example_results", package="breakpointRdata")
files2sync <- list.files(exampleFolder, full.names=TRUE)[1]
synchronizeReadDir(files2sync=files2sync)

Transform genomic coordinates

Description

Add two columns with transformed genomic coordinates to the GRanges-class object. This is useful for making genomewide plots.

Usage

transCoord(gr)
transCoord(gr)

Arguments

`gr`	A `GRanges-class` object.

Value

The input GRanges-class with two additional metadata columns 'start.genome' and 'end.genome'.

Write breakpointR configuration file

Description

Write an breakpointR configuration file from a list structure.

Usage

writeConfig(config, configfile)
writeConfig(config, configfile)

Arguments

`config`	A list structure with parameter values. Each entry will be written in one line.
`configfile`	Filename of the outputfile.

Value

NULL

Author(s)

Aaron Taudt

Package 'breakpointR'

Help Index

Breakpoint detection in Strand-Seq data

Description

Details

Author(s)

BreakPoint object

Description

Value

See Also

Main function for the breakpointR package

Description

Usage

Arguments

Value

Author(s)

Examples

Export UCSC browser formated files

Description

Usage

Arguments

Value

Author(s)

Examples

Find breakpoints from deltaWs

Description

Usage

Arguments

Value

Author(s)

Examples

Collapse consecutive bins with the same ID value

Description

Usage

Arguments

Value

Estimate confidence intervals for breakpoints

Description

Usage

Arguments

Value

Author(s)

Examples

Estimate confidence intervals for breakpoints

Description

Usage

Arguments

Value

Author(s)

Examples

Create composite Strand-seq file

Description

Usage

Arguments

Value

Author(s)

Calculate deltaWs

Description

Usage

Arguments

Value

Author(s)

See Also

Examples

Calculate deltaWs using various window sizes

Description

Usage

Arguments

Value

Author(s)

See Also

Function to print WC regions after breakpointR analysis

Description

Usage

Arguments

Value

Author(s)

Examples

Assign states to any given region using binomial test.

Description