@@ -1,7 +1,7 @@

 Package: chromstaR

 Type: Package

 Title: Combinatorial and Differential Chromatin State Analysis for ChIP-Seq Data

-Version: 1.5.1

+Version: 1.5.2

 Author: Aaron Taudt, Maria Colome Tatche, Matthias Heinig, Minh Anh Nguyen

 Maintainer: Aaron Taudt <aaron.taudt@gmail.com>

 Description: This package implements functions for combinatorial and differential analysis of ChIP-seq data. It includes uni- and multivariate peak-calling, export to genome browser viewable files, and functions for enrichment analyses.

@@ -4,23 +4,23 @@

 #'

 #' Convert aligned reads in .bam or .bed(.gz) format into read counts in equidistant windows.

 #'

-#' Convert aligned reads from .bam or .bed(.gz) files into read counts in equidistant windows (bins). This function uses \code{\link[GenomicRanges]{countOverlaps}} to calculate the read counts, or alternatively \code{\link[bamsignals]{bamProfile}} if option \code{use.bamsignals} is set (only effective for .bam files).

+#' Convert aligned reads from .bam or .bed(.gz) files into read counts in equidistant windows (bins). This function uses \code{GenomicRanges::countOverlaps} to calculate the read counts, or alternatively \code{bamsignals::bamProfile} if option \code{use.bamsignals} is set (only effective for .bam files).

 #'

 #' @aliases binning

-#' @param file A file with aligned reads. Alternatively a \code{\link{GRanges}} with aligned reads.

+#' @param file A file with aligned reads. Alternatively a \code{\link{GRanges-class}} with aligned reads.

 #' @param experiment.table An \code{\link{experiment.table}} containing the supplied \code{file}. This is necessary to uniquely identify the file in later steps of the workflow. Set to \code{NULL} if you don't have it (not recommended).

 #' @param ID Optional ID to select a row from the \code{experiment.table}. Only necessary if the experiment table contains the same file in multiple positions in column 'file'.

 #' @inheritParams readBamFileAsGRanges

 #' @inheritParams readBedFileAsGRanges

 #' @param binsizes An integer vector specifying the bin sizes to use.

 #' @param stepsizes An integer vector specifying the step size. One number can be given for each element in \code{binsizes}, \code{reads.per.bin} and \code{bins} (in that order).

-#' @param bins A \code{\link{GRanges}} or a named \code{list()} with \code{\link{GRanges}} containing precalculated bins produced by \code{\link{fixedWidthBins}} or \code{\link{variableWidthBins}}. Names of the list must correspond to the binsize. If the list is unnamed, an attempt is made to automatically determine the binsize.

+#' @param bins A \code{\link{GRanges-class}} or a named \code{list()} with \code{\link{GRanges-class}} containing precalculated bins produced by \code{\link{fixedWidthBins}} or \code{\link{variableWidthBins}}. Names of the list must correspond to the binsize. If the list is unnamed, an attempt is made to automatically determine the binsize.

 #' @param reads.per.bin Approximate number of desired reads per bin. The bin size will be selected accordingly.

 #' @param variable.width.reference A BAM file that is used as reference to produce variable width bins. See \code{\link{variableWidthBins}} for details.

 #' @param chromosomes If only a subset of the chromosomes should be binned, specify them here.

 #' @param use.bamsignals If \code{TRUE} the \pkg{\link[bamsignals]{bamsignals}} package is used for parsing of BAM files. This gives tremendous speed advantage for only one binsize but linearly increases for multiple binsizes, while \code{use.bamsignals=FALSE} has a binsize dependent runtime and might be faster if many binsizes are calculated.

 #' @param format One of \code{c('bed','bam','GRanges',NULL)}. With \code{NULL} the format is determined automatically from the file ending.

-#' @return If only one bin size was specified for option \code{binsizes}, the function returns a single \code{\link{GRanges}} object with meta data column 'counts' that contains the read count. If multiple \code{binsizes} were specified , the function returns a named \code{list()} of \link{GRanges} objects.

+#' @return If only one bin size was specified for option \code{binsizes}, the function returns a single \code{\link{GRanges-class}} object with meta data column 'counts' that contains the read count. If multiple \code{binsizes} were specified , the function returns a named \code{list()} of \link{GRanges-class} objects.

 #' @importFrom Rsamtools BamFile indexBam

 #' @importFrom bamsignals bamCount

 #' @export

@@ -4,8 +4,8 @@

 #'

 #' This function is similar to \code{\link{callPeaksUnivariateAllChr}} but allows to pre-fit on a single chromosome instead of the whole genome. This gives a significant performance increase and can help to converge into a better fit in case of unsteady quality for some chromosomes.

 #'

-#' @param binned.data A \code{\link{GRanges}} object with binned read counts or a file that contains such an object.

-#' @param control.data Input control for the experiment. A \code{\link{GRanges}} object with binned read counts or a file that contains such an object.

+#' @param binned.data A \code{\link{GRanges-class}} object with binned read counts or a file that contains such an object.

+#' @param control.data Input control for the experiment. A \code{\link{GRanges-class}} object with binned read counts or a file that contains such an object.

 #' @param prefit.on.chr A chromosome that is used to pre-fit the Hidden Markov Model. Set to \code{NULL} if you don't want to prefit but use the whole genome instead.

 #' @param short If \code{TRUE}, the second fitting step is only done with one iteration.

 #' @param eps Convergence threshold for the Baum-Welch algorithm.

@@ -121,8 +121,8 @@ callPeaksUnivariate <- function(binned.data, control.data=NULL, prefit.on.chr=NU

 #'

 #' The Hidden Markov Model which is used to classify the bins uses 3 states: state 'zero-inflation' with a delta function as emission densitiy (only zero read counts), 'unmodified' and 'modified' with Negative Binomials as emission densities. A Baum-Welch algorithm is employed to estimate the parameters of the distributions. Please refer to our manuscript at \url{http://dx.doi.org/10.1101/038612} for a detailed description of the method.

 #'

-#' @param binned.data A \code{\link{GRanges}} object with binned read counts or a file that contains such an object.

-#' @param control.data Input control for the experiment. A \code{\link{GRanges}} object with binned read counts or a file that contains such an object.

+#' @param binned.data A \code{\link{GRanges-class}} object with binned read counts or a file that contains such an object.

+#' @param control.data Input control for the experiment. A \code{\link{GRanges-class}} object with binned read counts or a file that contains such an object.

 #' @param eps Convergence threshold for the Baum-Welch algorithm.

 #' @param init One of the following initialization procedures:

 #' \describe{

@@ -84,7 +84,7 @@ NULL

 #' Binned read counts

 #'

-#' A \code{\link[GenomicRanges]{GRanges}} object which contains binned read counts as meta data column \code{counts}. It is output of the \code{\link{binReads}} function.

+#' A \code{\link[GenomicRanges]{GRanges-class}} object which contains binned read counts as meta data column \code{counts}. It is output of the \code{\link{binReads}} function.

 #' @name binned.data

 NULL

@@ -96,9 +96,9 @@ NULL

 #' @return

 #' A \code{list()} with the following entries:

 #' \item{info}{Experiment table for this object.}

-#' \item{bincounts}{A \code{\link[GenomicRanges]{GRanges}} object containing the genomic bin coordinates and original binned read count values for different offsets.}

-#' \item{bins}{A \code{\link[GenomicRanges]{GRanges}} object containing the genomic bin coordinates, their read count, (optional) posteriors and state classification.}

-#' \item{peaks}{A \code{list()} with \code{\link[GenomicRanges]{GRanges}} containing peak coordinates for each ID in \code{info}.}

+#' \item{bincounts}{A \code{\link[GenomicRanges]{GRanges-class}} object containing the genomic bin coordinates and original binned read count values for different offsets.}

+#' \item{bins}{A \code{\link[GenomicRanges]{GRanges-class}} object containing the genomic bin coordinates, their read count, (optional) posteriors and state classification.}

+#' \item{peaks}{A \code{list()} with \code{\link[GenomicRanges]{GRanges-class}} containing peak coordinates for each ID in \code{info}.}

 #' \item{weights}{Weight for each component. Same as \code{apply(hmm$posteriors,2,mean)}.}

 #' \item{transitionProbs}{Matrix of transition probabilities from each state (row) into each state (column).}

 #' \item{transitionProbs.initial}{Initial \code{transitionProbs} at the beginning of the Baum-Welch.}

@@ -127,10 +127,10 @@ NULL

 #' @return

 #' A \code{list()} with the following entries:

 #' \item{info}{Experiment table for this object.}

-#' \item{bincounts}{A \code{\link[GenomicRanges]{GRanges}} object containing the genomic bin coordinates and original binned read count values for different offsets.}

-#' \item{bins}{A \code{\link[GenomicRanges]{GRanges}} object containing the genomic bin coordinates, their read count, (optional) posteriors and state classification.}

+#' \item{bincounts}{A \code{\link[GenomicRanges]{GRanges-class}} object containing the genomic bin coordinates and original binned read count values for different offsets.}

+#' \item{bins}{A \code{\link[GenomicRanges]{GRanges-class}} object containing the genomic bin coordinates, their read count, (optional) posteriors and state classification.}

 #' \item{segments}{Same as \code{bins}, but consecutive bins with the same state are collapsed into segments.}

-#' \item{peaks}{A \code{list()} with \code{\link[GenomicRanges]{GRanges}} containing peak coordinates for each ID in \code{info}.}

+#' \item{peaks}{A \code{list()} with \code{\link[GenomicRanges]{GRanges-class}} containing peak coordinates for each ID in \code{info}.}

 #' \item{mapping}{A named vector giving the mapping from decimal combinatorial states to human readable combinations.}

 #' \item{weights}{Weight for each component. Same as \code{apply(hmm$posteriors,2,mean)}.}

 #' \item{weights.univariate}{Weights of the univariate HMMs.}

@@ -164,10 +164,10 @@ NULL

 #' @return

 #' A \code{list()} with the following entries:

 #' \item{info}{Experiment table for this object.}

-#' \item{bins}{A \code{\link[GenomicRanges]{GRanges}} object containing genomic bin coordinates and human readable combinations for the combined \code{\link{multiHMM}} objects.}

+#' \item{bins}{A \code{\link[GenomicRanges]{GRanges-class}} object containing genomic bin coordinates and human readable combinations for the combined \code{\link{multiHMM}} objects.}

 #' \item{segments}{Same as \code{bins}, but consecutive bins with the same state are collapsed into segments.}

 #' \item{segments.per.condition}{A \code{list()} with segments for each condition separately.}

-#' \item{peaks}{A \code{list()} with \code{\link[GenomicRanges]{GRanges}} containing peak coordinates for each ID in \code{info}.}

+#' \item{peaks}{A \code{list()} with \code{\link[GenomicRanges]{GRanges-class}} containing peak coordinates for each ID in \code{info}.}

 #' \item{frequencies}{Genomic frequencies of combinations.}

 #' \item{mode}{Mode of analysis.}

 #' @seealso \code{\link{combineMultivariates}}, \code{\link{uniHMM}}, \code{\link{multiHMM}}

@@ -1,6 +1,6 @@

 #' Enrichment analysis

 #' 

-#' Plotting functions for enrichment analysis of \code{\link{multiHMM}} or \code{\link{combinedMultiHMM}} objects with any annotation of interest, specified as a \code{\link[GenomicRanges]{GRanges}} object.

+#' Plotting functions for enrichment analysis of \code{\link{multiHMM}} or \code{\link{combinedMultiHMM}} objects with any annotation of interest, specified as a \code{\link[GenomicRanges]{GRanges-class}} object.

 #' 

 #' @name enrichment_analysis

 #' @param combinations A vector with combinations for which the enrichment will be calculated. If \code{NULL} all combinations will be considered.

@@ -64,7 +64,7 @@ NULL

 #' @describeIn enrichment_analysis Compute the fold enrichment of combinatorial states for multiple annotations.

 #' @param hmm A \code{\link{combinedMultiHMM}} or \code{\link{multiHMM}} object or a file that contains such an object.

-#' @param annotations A \code{list()} with \code{\link{GRanges}} objects containing coordinates of multiple annotations The names of the list entries will be used to name the return values.

+#' @param annotations A \code{list()} with \code{\link{GRanges-class}} objects containing coordinates of multiple annotations The names of the list entries will be used to name the return values.

 #' @param plot A logical indicating whether the plot or an array with the fold enrichment values is returned.

 #' @param what One of \code{c('combinations','peaks','counts','transitions')} specifying on which feature the statistic is calculated.

 #' @importFrom S4Vectors subjectHits queryHits

@@ -575,12 +575,12 @@ plotEnrichment <- function(hmm, annotation, bp.around.annotation=10000, region=c

 #' Enrichment of (combinatorial) states for genomic annotations

 #'

-#' The function calculates the enrichment of a genomic feature with peaks or combinatorial states. Input is a \code{\link{multiHMM}} object (containing the peak calls and combinatorial states) and a \code{\link{GRanges}} object containing the annotation of interest (e.g. transcription start sites or genes).

+#' The function calculates the enrichment of a genomic feature with peaks or combinatorial states. Input is a \code{\link{multiHMM}} object (containing the peak calls and combinatorial states) and a \code{\link{GRanges-class}} object containing the annotation of interest (e.g. transcription start sites or genes).

 #'

 #' @author Aaron Taudt

 #' @param bins The \code{$bins} entry from a \code{\link{multiHMM}} or \code{\link{combinedMultiHMM}} object.

 #' @param info The \code{$info} entry from a \code{\link{multiHMM}} or \code{\link{combinedMultiHMM}} object.

-#' @param annotation A \code{\link{GRanges}} object with the annotation of interest.

+#' @param annotation A \code{\link{GRanges-class}} object with the annotation of interest.

 #' @param bp.around.annotation An integer specifying the number of basepairs up- and downstream of the annotation for which the enrichment will be calculated.

 #' @param region A combination of \code{c('start','inside','end')} specifying the region of the annotation for which the enrichment will be calculated. Select \code{'start'} if you have a point-sized annotation like transcription start sites. Select \code{c('start','inside','end')} if you have long annotations like genes.

 #' @param what One of \code{c('combinations','peaks','counts')} specifying on which feature the statistic is calculated.

@@ -841,10 +841,10 @@ exportCombinedMultivariateCounts <- function(hmm, filename, header=TRUE, separat

 #'

 #' Export GRanges as genome browser viewable file

 #'

-#' Export regions from \code{\link{GRanges}} as a file which can be uploaded into a genome browser. Regions are exported in BED format (.bed.gz).

+#' Export regions from \code{\link{GRanges-class}} as a file which can be uploaded into a genome browser. Regions are exported in BED format (.bed.gz).

 #'

 #' @author Aaron Taudt

-#' @param gr A \code{\link{GRanges}} object.

+#' @param gr A \code{\link{GRanges-class}} object.

 #' @param trackname The name that will be used as track name and description in the header.

 #' @param filename The name of the file that will be written. The ending ".bed.gz". Any existing file will be overwritten.

 #' @param namecol A character specifying the column that is used as name-column.

@@ -3,7 +3,7 @@

 #' Get the expression values that overlap with each combinatorial state.

 #'

 #' @param hmm A \code{\link{multiHMM}} or \code{\link{combinedMultiHMM}} object or file that contains such an object.

-#' @param expression A \code{\link{GRanges}} object with metadata column 'expression', containing the expression value for each range.

+#' @param expression A \code{\link{GRanges-class}} object with metadata column 'expression', containing the expression value for each range.

 #' @param combinations A vector with combinations for which the expression overlap will be calculated. If \code{NULL} all combinations will be considered.

 #' @param return.marks Set to \code{TRUE} if expression values for marks instead of combinations should be returned.

 #' @return A \code{\link{ggplot2}} object if a \code{\link{multiHMM}} was given or a named list with \code{\link{ggplot2}} objects if a \code{\link{combinedMultiHMM}} was given.

@@ -109,7 +109,7 @@ plotExpression <- function(hmm, expression, combinations=NULL, return.marks=FALS

 # #' Get the average expression for each percentage of overlap of combinatorial state with feature.

 # #'

 # #' @param multi.hmm A \code{\link{multiHMM}} or a file that contains such an object.

-# #' @param expression A \code{\link{GRanges}} object with metadata column 'expression', containing the expression value for each range of the feature.

+# #' @param expression A \code{\link{GRanges-class}} object with metadata column 'expression', containing the expression value for each range of the feature.

 # #' @param combinations A vector with combinations for which the expression overlap will be calculated. If \code{NULL} all combinations will be considered.

 # #' @return A list with vectors of mean expression values per percentile for each combinatorial state. 

 # #' @author Aaron Taudt

@@ -1,8 +1,8 @@

 #' Get combinations

 #' 

-#' Get a DataFrame with combinations from a \code{\link[GenomicRanges]{GRanges}} object.

+#' Get a DataFrame with combinations from a \code{\link[GenomicRanges]{GRanges-class}} object.

 #' 

-#' @param gr A \code{\link[GenomicRanges]{GRanges}} object from which the meta-data columns containing combinations will be extracted.

+#' @param gr A \code{\link[GenomicRanges]{GRanges-class}} object from which the meta-data columns containing combinations will be extracted.

 #' @return A DataFrame.

 #' 

 #' @export

@@ -2,7 +2,7 @@

 #' Import BAM file into GRanges

 #'

-#' Import aligned reads from a BAM file into a \code{\link{GRanges}} object.

+#' Import aligned reads from a BAM file into a \code{\link{GRanges-class}} object.

 #'

 #' @param bamfile A sorted BAM file.

 #' @param bamindex BAM index file. Can be specified without the .bai ending. If the index file does not exist it will be created and a warning is issued.

@@ -11,9 +11,9 @@

 #' @param remove.duplicate.reads A logical indicating whether or not duplicate reads should be removed.

 #' @param min.mapq Minimum mapping quality when importing from BAM files. Set \code{min.mapq=0} to keep all reads.

 #' @param max.fragment.width Maximum allowed fragment length. This is to filter out erroneously wrong fragments due to mapping errors of paired end reads.

-#' @param blacklist A \code{\link{GRanges}} or a bed(.gz) file with blacklisted regions. Reads falling into those regions will be discarded.

-#' @param what A character vector of fields that are returned. Type \code{\link[Rsamtools]{scanBamWhat}} to see what is available.

-#' @return A \code{\link{GRanges}} object containing the reads.

+#' @param blacklist A \code{\link{GRanges-class}} or a bed(.gz) file with blacklisted regions. Reads falling into those regions will be discarded.

+#' @param what A character vector of fields that are returned. Uses the \code{Rsamtools::scanBamWhat} function. See \code{\link[Rsamtools]{ScanBamParam}} to see what is available.

+#' @return A \code{\link{GRanges-class}} object containing the reads.

 #' @importFrom Rsamtools indexBam BamFile ScanBamParam scanBamFlag

 #' @importFrom GenomicAlignments readGAlignmentPairs readGAlignments first

 #' @importFrom S4Vectors queryHits

@@ -178,7 +178,7 @@ readBamFileAsGRanges <- function(bamfile, bamindex=bamfile, chromosomes=NULL, pa

 #' Import BED file into GRanges

 #'

-#' Import aligned reads from a BED file into a \code{\link{GRanges}} object.

+#' Import aligned reads from a BED file into a \code{\link{GRanges-class}} object.

 #'

 #' @param bedfile A file with aligned reads in BED-6 format. The columns have to be c('chromosome','start','end','description','mapq','strand').

 #' @param assembly Please see \code{\link[GenomeInfoDb]{fetchExtendedChromInfoFromUCSC}} for available assemblies. Only necessary when importing BED files. BAM files are handled automatically. Alternatively a data.frame with columns 'chromosome' and 'length'.

@@ -186,8 +186,8 @@ readBamFileAsGRanges <- function(bamfile, bamindex=bamfile, chromosomes=NULL, pa

 #' @param remove.duplicate.reads A logical indicating whether or not duplicate reads should be removed.

 #' @param min.mapq Minimum mapping quality when importing from BAM files. Set \code{min.mapq=0} to keep all reads.

 #' @param max.fragment.width Maximum allowed fragment length. This is to filter out erroneously wrong fragments.

-#' @param blacklist A \code{\link{GRanges}} or a bed(.gz) file with blacklisted regions. Reads falling into those regions will be discarded.

-#' @return A \code{\link{GRanges}} object containing the reads.

+#' @param blacklist A \code{\link{GRanges-class}} or a bed(.gz) file with blacklisted regions. Reads falling into those regions will be discarded.

+#' @return A \code{\link{GRanges-class}} object containing the reads.

 #' @importFrom utils read.table

 #' @importFrom S4Vectors queryHits

 #' @export

@@ -8,7 +8,7 @@

 #' @param chromosome.format A character specifying the format of the chromosomes if \code{assembly} is specified. Either 'NCBI' for (1,2,3 ...) or 'UCSC' for (chr1,chr2,chr3 ...). If a \code{bamfile} or \code{chrom.lengths} is supplied, the format will be chosen automatically.

 #' @param binsizes A vector of bin sizes in base pairs.

 #' @param chromosomes A subset of chromosomes for which the bins are generated.

-#' @return A \code{list()} of \code{\link{GRanges}} objects with fixed-width bins.

+#' @return A \code{list()} of \code{\link{GRanges-class}} objects with fixed-width bins.

 #' @author Aaron Taudt

 #' @importFrom Rsamtools BamFile

 #' @export

@@ -116,10 +116,10 @@ fixedWidthBins <- function(bamfile=NULL, assembly=NULL, chrom.lengths=NULL, chro

 #' 

 #' Variable-width bins are produced by first binning the reference BAM file with fixed-width bins and selecting the desired number of reads per bin as the (non-zero) maximum of the histogram. A new set of bins is then generated such that every bin contains the desired number of reads.

 #' 

-#' @param reads A \code{\link{GRanges}} with reads. See \code{\link{readBamFileAsGRanges}} and \code{\link{readBedFileAsGRanges}}.

+#' @param reads A \code{\link{GRanges-class}} with reads. See \code{\link{readBamFileAsGRanges}} and \code{\link{readBedFileAsGRanges}}.

 #' @param binsizes A vector with binsizes. Resulting bins will be close to the specified binsizes.

 #' @param chromosomes A subset of chromosomes for which the bins are generated.

-#' @return A \code{list()} of \code{\link{GRanges}} objects with variable-width bins.

+#' @return A \code{list()} of \code{\link{GRanges-class}} objects with variable-width bins.

 #' @author Aaron Taudt

 #' @export

 #'

@@ -356,8 +356,8 @@ plotBoxplot <- function(model) {

 #' #' 

 #' #' Plot a simple genome browser view. This is useful for scripted genome browser snapshots.

 #' #' 

-#' #' @param counts A \code{\link[GenomicRanges]{GRanges}} object with meta-data column 'counts'.

-#' #' @param peaklist A named list() of \code{\link[GenomicRanges]{GRanges}} objects containing peak coordinates.

+#' #' @param counts A \code{\link[GenomicRanges]{GRanges-class}} object with meta-data column 'counts'.

+#' #' @param peaklist A named list() of \code{\link[GenomicRanges]{GRanges-class}} objects containing peak coordinates.

 #' #' @param chr,start,end Chromosome, start and end coordinates for the plot.

 #' #' @param countcol A character giving the color for the counts.

 #' #' @param peakcols A character vector with colors for the peaks in \code{peaklist}.

@@ -2,7 +2,7 @@

 #' Read bed-file into GRanges

 #'

-#' This is a simple convenience function to read a bed(.gz)-file into a \code{\link{GRanges}} object. The bed-file is expected to have the following fields: \code{chromosome, start, end, name, score, strand}.

+#' This is a simple convenience function to read a bed(.gz)-file into a \code{\link{GRanges-class}} object. The bed-file is expected to have the following fields: \code{chromosome, start, end, name, score, strand}.

 #'

 #' @param bedfile Filename of the bed or bed.gz file.

 #' @param col.names A character vector giving the names of the columns in the \code{bedfile}. Must contain at least \code{c('chromosome','start','end')}.

@@ -10,7 +10,7 @@

 #' @param skip Number of lines to skip at the beginning.

 #' @param chromosome.format Desired format of the chromosomes. Either 'NCBI' for (1,2,3 ...) or 'UCSC' for (chr1,chr2,chr3 ...) or \code{NULL} to keep the original names.

 #' @param sep Field separator from \code{\link{read.table}}.

-#' @return A \code{\link{GRanges}} object with the contents of the bed-file.

+#' @return A \code{\link{GRanges-class}} object with the contents of the bed-file.

 #' @author Aaron Taudt

 #' @importFrom utils read.table

 #' @export

@@ -2,9 +2,9 @@

 #'

 #' Make segmentation from bins for a \code{\link{multiHMM}} object.

 #'

-#' @param bins A \code{\link[GenomicRanges]{GRanges}} with binned read counts.

+#' @param bins A \code{\link[GenomicRanges]{GRanges-class}} with binned read counts.

 #' @inheritParams collapseBins

-#' @return A \code{\link[GenomicRanges]{GRanges}} with segmented regions.

+#' @return A \code{\link[GenomicRanges]{GRanges-class}} with segmented regions.

 #'

 multivariateSegmentation <- function(bins, column2collapseBy='state') {

@@ -2,7 +2,7 @@

 #' 

 #' Simulate known states, read counts and read coordinates using a univariate Hidden Markov Model with three states ("zero-inflation", "unmodified" and "modified").

 #' 

-#' @param bins A \code{\link[GenomicRanges]{GRanges}} object for which reads will be simulated.

+#' @param bins A \code{\link[GenomicRanges]{GRanges-class}} object for which reads will be simulated.

 #' @param transition A matrix with transition probabilities.

 #' @param emission A data.frame with emission distributions (see \code{\link{uniHMM}} entry 'distributions').

 #' @inheritParams simulateReadsFromCounts

@@ -70,9 +70,9 @@ simulateUnivariate <- function(bins, transition, emission, fragLen=50) {

 #' 

 #' Simulate read coordinates using read counts as input.

 #' 

-#' @param bins A \code{\link[GenomicRanges]{GRanges}} with read counts.

+#' @param bins A \code{\link[GenomicRanges]{GRanges-class}} with read counts.

 #' @param fragLen Length of the simulated read fragments.

-#' @return A \code{\link[GenomicRanges]{GRanges}} with read coordinates.

+#' @return A \code{\link[GenomicRanges]{GRanges-class}} with read coordinates.

 simulateReadsFromCounts <- function(bins, fragLen=50) {

     ptm <- startTimedMessage("Generating read coordinates ...")

@@ -115,7 +115,7 @@ simulateReadsFromCounts <- function(bins, fragLen=50) {

 #' 

 #' Simulate known states, read counts and read coordinates using a multivariate Hidden Markov Model.

 #' 

-#' @param bins A \code{\link[GenomicRanges]{GRanges}} object for which reads will be simulated.

+#' @param bins A \code{\link[GenomicRanges]{GRanges-class}} object for which reads will be simulated.

 #' @param transition A matrix with transition probabilities.

 #' @param emissions A list() with data.frames with emission distributions (see \code{\link{uniHMM}} entry 'distributions').

 #' @param weights A list() with weights for the three univariate states.

@@ -3,9 +3,9 @@

 #' Normalize read counts to a given read depth. Reads counts are randomly removed from the input to match the specified read depth.

 #'

 #' @author Aaron Taudt

-#' @param binned.data A \code{\link{GRanges}} object with meta data column 'reads' that contains the read count.

+#' @param binned.data A \code{\link{GRanges-class}} object with meta data column 'reads' that contains the read count.

 #' @param sample.reads The number of reads that will be retained.

-#' @return A \code{\link{GRanges}} object with downsampled read counts.

+#' @return A \code{\link{GRanges-class}} object with downsampled read counts.

 #' @importFrom stats rbinom

 subsample <- function(binned.data, sample.reads) {

@@ -13,7 +13,7 @@ binReads(file, experiment.table = NULL, ID = NULL, assembly,

   use.bamsignals = TRUE, format = NULL)

 }

 \arguments{

-\item{file}{A file with aligned reads. Alternatively a \code{\link{GRanges}} with aligned reads.}

+\item{file}{A file with aligned reads. Alternatively a \code{\link{GRanges-class}} with aligned reads.}

 \item{experiment.table}{An \code{\link{experiment.table}} containing the supplied \code{file}. This is necessary to uniquely identify the file in later steps of the workflow. Set to \code{NULL} if you don't have it (not recommended).}

@@ -33,7 +33,7 @@ binReads(file, experiment.table = NULL, ID = NULL, assembly,

 \item{max.fragment.width}{Maximum allowed fragment length. This is to filter out erroneously wrong fragments due to mapping errors of paired end reads.}

-\item{blacklist}{A \code{\link{GRanges}} or a bed(.gz) file with blacklisted regions. Reads falling into those regions will be discarded.}

+\item{blacklist}{A \code{\link{GRanges-class}} or a bed(.gz) file with blacklisted regions. Reads falling into those regions will be discarded.}

 \item{binsizes}{An integer vector specifying the bin sizes to use.}

@@ -41,7 +41,7 @@ binReads(file, experiment.table = NULL, ID = NULL, assembly,

 \item{reads.per.bin}{Approximate number of desired reads per bin. The bin size will be selected accordingly.}

-\item{bins}{A \code{\link{GRanges}} or a named \code{list()} with \code{\link{GRanges}} containing precalculated bins produced by \code{\link{fixedWidthBins}} or \code{\link{variableWidthBins}}. Names of the list must correspond to the binsize. If the list is unnamed, an attempt is made to automatically determine the binsize.}

+\item{bins}{A \code{\link{GRanges-class}} or a named \code{list()} with \code{\link{GRanges-class}} containing precalculated bins produced by \code{\link{fixedWidthBins}} or \code{\link{variableWidthBins}}. Names of the list must correspond to the binsize. If the list is unnamed, an attempt is made to automatically determine the binsize.}

 \item{variable.width.reference}{A BAM file that is used as reference to produce variable width bins. See \code{\link{variableWidthBins}} for details.}

@@ -50,13 +50,13 @@ binReads(file, experiment.table = NULL, ID = NULL, assembly,

 \item{format}{One of \code{c('bed','bam','GRanges',NULL)}. With \code{NULL} the format is determined automatically from the file ending.}

 }

 \value{

-If only one bin size was specified for option \code{binsizes}, the function returns a single \code{\link{GRanges}} object with meta data column 'counts' that contains the read count. If multiple \code{binsizes} were specified , the function returns a named \code{list()} of \link{GRanges} objects.

+If only one bin size was specified for option \code{binsizes}, the function returns a single \code{\link{GRanges-class}} object with meta data column 'counts' that contains the read count. If multiple \code{binsizes} were specified , the function returns a named \code{list()} of \link{GRanges-class} objects.

 }

 \description{

 Convert aligned reads in .bam or .bed(.gz) format into read counts in equidistant windows.

 }

 \details{

-Convert aligned reads from .bam or .bed(.gz) files into read counts in equidistant windows (bins). This function uses \code{\link[GenomicRanges]{countOverlaps}} to calculate the read counts, or alternatively \code{\link[bamsignals]{bamProfile}} if option \code{use.bamsignals} is set (only effective for .bam files).

+Convert aligned reads from .bam or .bed(.gz) files into read counts in equidistant windows (bins). This function uses \code{GenomicRanges::countOverlaps} to calculate the read counts, or alternatively \code{bamsignals::bamProfile} if option \code{use.bamsignals} is set (only effective for .bam files).

 }

 \examples{

 ## Get an example BAM file with ChIP-seq reads

@@ -4,5 +4,5 @@

 \alias{binned.data}

 \title{Binned read counts}

 \description{

-A \code{\link[GenomicRanges]{GRanges}} object which contains binned read counts as meta data column \code{counts}. It is output of the \code{\link{binReads}} function.

+A \code{\link[GenomicRanges]{GRanges-class}} object which contains binned read counts as meta data column \code{counts}. It is output of the \code{\link{binReads}} function.

 }

@@ -13,9 +13,9 @@ callPeaksUnivariate(binned.data, control.data = NULL, prefit.on.chr = NULL,

   verbosity = 1)

 }

 \arguments{

-\item{binned.data}{A \code{\link{GRanges}} object with binned read counts or a file that contains such an object.}

+\item{binned.data}{A \code{\link{GRanges-class}} object with binned read counts or a file that contains such an object.}

-\item{control.data}{Input control for the experiment. A \code{\link{GRanges}} object with binned read counts or a file that contains such an object.}

+\item{control.data}{Input control for the experiment. A \code{\link{GRanges-class}} object with binned read counts or a file that contains such an object.}

 \item{prefit.on.chr}{A chromosome that is used to pre-fit the Hidden Markov Model. Set to \code{NULL} if you don't want to prefit but use the whole genome instead.}

@@ -12,9 +12,9 @@ callPeaksUnivariateAllChr(binned.data, control.data = NULL, eps = 0.01,

   keep.densities = FALSE, verbosity = 1)

 }

 \arguments{

-\item{binned.data}{A \code{\link{GRanges}} object with binned read counts or a file that contains such an object.}

+\item{binned.data}{A \code{\link{GRanges-class}} object with binned read counts or a file that contains such an object.}

-\item{control.data}{Input control for the experiment. A \code{\link{GRanges}} object with binned read counts or a file that contains such an object.}

+\item{control.data}{Input control for the experiment. A \code{\link{GRanges-class}} object with binned read counts or a file that contains such an object.}

 \item{eps}{Convergence threshold for the Baum-Welch algorithm.}

@@ -7,10 +7,10 @@

 \value{

 A \code{list()} with the following entries:

 \item{info}{Experiment table for this object.}

-\item{bins}{A \code{\link[GenomicRanges]{GRanges}} object containing genomic bin coordinates and human readable combinations for the combined \code{\link{multiHMM}} objects.}

+\item{bins}{A \code{\link[GenomicRanges]{GRanges-class}} object containing genomic bin coordinates and human readable combinations for the combined \code{\link{multiHMM}} objects.}

 \item{segments}{Same as \code{bins}, but consecutive bins with the same state are collapsed into segments.}

 \item{segments.per.condition}{A \code{list()} with segments for each condition separately.}

-\item{peaks}{A \code{list()} with \code{\link[GenomicRanges]{GRanges}} containing peak coordinates for each ID in \code{info}.}

+\item{peaks}{A \code{list()} with \code{\link[GenomicRanges]{GRanges-class}} containing peak coordinates for each ID in \code{info}.}

 \item{frequencies}{Genomic frequencies of combinations.}

 \item{mode}{Mode of analysis.}

 }

@@ -13,7 +13,7 @@ enrichmentAtAnnotation(bins, info, annotation, bp.around.annotation = 10000,

 \item{info}{The \code{$info} entry from a \code{\link{multiHMM}} or \code{\link{combinedMultiHMM}} object.}

-\item{annotation}{A \code{\link{GRanges}} object with the annotation of interest.}

+\item{annotation}{A \code{\link{GRanges-class}} object with the annotation of interest.}

 \item{bp.around.annotation}{An integer specifying the number of basepairs up- and downstream of the annotation for which the enrichment will be calculated.}

@@ -29,7 +29,7 @@ enrichmentAtAnnotation(bins, info, annotation, bp.around.annotation = 10000,

 A \code{list()} containing \code{data.frame()}s for enrichment of combinatorial states and binary states at the start, end and inside of the annotation.

 }

 \description{

-The function calculates the enrichment of a genomic feature with peaks or combinatorial states. Input is a \code{\link{multiHMM}} object (containing the peak calls and combinatorial states) and a \code{\link{GRanges}} object containing the annotation of interest (e.g. transcription start sites or genes).

+The function calculates the enrichment of a genomic feature with peaks or combinatorial states. Input is a \code{\link{multiHMM}} object (containing the peak calls and combinatorial states) and a \code{\link{GRanges-class}} object containing the annotation of interest (e.g. transcription start sites or genes).

 }

 \author{

 Aaron Taudt

@@ -23,7 +23,7 @@ plotEnrichment(hmm, annotation, bp.around.annotation = 10000,

 \arguments{

 \item{hmm}{A \code{\link{combinedMultiHMM}} or \code{\link{multiHMM}} object or a file that contains such an object.}

-\item{annotations}{A \code{list()} with \code{\link{GRanges}} objects containing coordinates of multiple annotations The names of the list entries will be used to name the return values.}

+\item{annotations}{A \code{list()} with \code{\link{GRanges-class}} objects containing coordinates of multiple annotations The names of the list entries will be used to name the return values.}

 \item{what}{One of \code{c('combinations','peaks','counts','transitions')} specifying on which feature the statistic is calculated.}

@@ -35,7 +35,7 @@ plotEnrichment(hmm, annotation, bp.around.annotation = 10000,

 \item{logscale}{Set to \code{TRUE} to plot fold enrichment on log-scale. Ignored if \code{statistic = 'fraction'}.}

-\item{annotation}{A \code{\link{GRanges}} object with the annotation of interest.}

+\item{annotation}{A \code{\link{GRanges-class}} object with the annotation of interest.}

 \item{bp.around.annotation}{An integer specifying the number of basepairs up- and downstream of the annotation for which the enrichment will be calculated.}

@@ -57,7 +57,7 @@ plotEnrichment(hmm, annotation, bp.around.annotation = 10000,

 A \code{\link[ggplot2:ggplot]{ggplot}} object containing the plot or a list() with \code{\link[ggplot2:ggplot]{ggplot}} objects if several plots are returned. For \code{plotFoldEnrichHeatmap} a named array with fold enrichments if \code{plot=FALSE}.

 }

 \description{

-Plotting functions for enrichment analysis of \code{\link{multiHMM}} or \code{\link{combinedMultiHMM}} objects with any annotation of interest, specified as a \code{\link[GenomicRanges]{GRanges}} object.

+Plotting functions for enrichment analysis of \code{\link{multiHMM}} or \code{\link{combinedMultiHMM}} objects with any annotation of interest, specified as a \code{\link[GenomicRanges]{GRanges-class}} object.

 }

 \section{Functions}{

 \itemize{

@@ -9,7 +9,7 @@ exportGRangesAsBedFile(gr, trackname, filename, namecol = "combination",

   append = FALSE)

 }

 \arguments{

-\item{gr}{A \code{\link{GRanges}} object.}

+\item{gr}{A \code{\link{GRanges-class}} object.}

 \item{trackname}{The name that will be used as track name and description in the header.}

@@ -34,7 +34,7 @@ exportGRangesAsBedFile(gr, trackname, filename, namecol = "combination",

 Export GRanges as genome browser viewable file

 }

 \details{

-Export regions from \code{\link{GRanges}} as a file which can be uploaded into a genome browser. Regions are exported in BED format (.bed.gz).

+Export regions from \code{\link{GRanges-class}} as a file which can be uploaded into a genome browser. Regions are exported in BED format (.bed.gz).

 }

 \examples{

 ### Export regions with read counts above 20 ###

@@ -21,7 +21,7 @@ fixedWidthBins(bamfile = NULL, assembly = NULL, chrom.lengths = NULL,

 \item{chromosomes}{A subset of chromosomes for which the bins are generated.}

 }

 \value{

-A \code{list()} of \code{\link{GRanges}} objects with fixed-width bins.

+A \code{list()} of \code{\link{GRanges-class}} objects with fixed-width bins.

 }

 \description{

 Make fixed-width bins based on given bin size.

@@ -7,13 +7,13 @@

 getCombinations(gr)

 }

 \arguments{

-\item{gr}{A \code{\link[GenomicRanges]{GRanges}} object from which the meta-data columns containing combinations will be extracted.}

+\item{gr}{A \code{\link[GenomicRanges]{GRanges-class}} object from which the meta-data columns containing combinations will be extracted.}

 }

 \value{

 A DataFrame.

 }

 \description{

-Get a DataFrame with combinations from a \code{\link[GenomicRanges]{GRanges}} object.

+Get a DataFrame with combinations from a \code{\link[GenomicRanges]{GRanges-class}} object.

 }

 \examples{

 ### Get an example multiHMM ###

@@ -7,10 +7,10 @@

 \value{

 A \code{list()} with the following entries:

 \item{info}{Experiment table for this object.}

-\item{bincounts}{A \code{\link[GenomicRanges]{GRanges}} object containing the genomic bin coordinates and original binned read count values for different offsets.}

-\item{bins}{A \code{\link[GenomicRanges]{GRanges}} object containing the genomic bin coordinates, their read count, (optional) posteriors and state classification.}

+\item{bincounts}{A \code{\link[GenomicRanges]{GRanges-class}} object containing the genomic bin coordinates and original binned read count values for different offsets.}

+\item{bins}{A \code{\link[GenomicRanges]{GRanges-class}} object containing the genomic bin coordinates, their read count, (optional) posteriors and state classification.}

 \item{segments}{Same as \code{bins}, but consecutive bins with the same state are collapsed into segments.}

-\item{peaks}{A \code{list()} with \code{\link[GenomicRanges]{GRanges}} containing peak coordinates for each ID in \code{info}.}

+\item{peaks}{A \code{list()} with \code{\link[GenomicRanges]{GRanges-class}} containing peak coordinates for each ID in \code{info}.}

 \item{mapping}{A named vector giving the mapping from decimal combinatorial states to human readable combinations.}

 \item{weights}{Weight for each component. Same as \code{apply(hmm$posteriors,2,mean)}.}

 \item{weights.univariate}{Weights of the univariate HMMs.}

@@ -7,12 +7,12 @@

 multivariateSegmentation(bins, column2collapseBy = "state")

 }

 \arguments{

-\item{bins}{A \code{\link[GenomicRanges]{GRanges}} with binned read counts.}

+\item{bins}{A \code{\link[GenomicRanges]{GRanges-class}} with binned read counts.}

 \item{column2collapseBy}{The number of the column which will be used to collapse all other inputs. If a set of consecutive bins has the same value in this column, they will be aggregated into one bin with adjusted genomic coordinates.}

 }

 \value{

-A \code{\link[GenomicRanges]{GRanges}} with segmented regions.

+A \code{\link[GenomicRanges]{GRanges-class}} with segmented regions.

 }

 \description{

 Make segmentation from bins for a \code{\link{multiHMM}} object.

@@ -9,7 +9,7 @@ plotExpression(hmm, expression, combinations = NULL, return.marks = FALSE)

 \arguments{

 \item{hmm}{A \code{\link{multiHMM}} or \code{\link{combinedMultiHMM}} object or file that contains such an object.}

-\item{expression}{A \code{\link{GRanges}} object with metadata column 'expression', containing the expression value for each range.}

+\item{expression}{A \code{\link{GRanges-class}} object with metadata column 'expression', containing the expression value for each range.}

 \item{combinations}{A vector with combinations for which the expression overlap will be calculated. If \code{NULL} all combinations will be considered.}

@@ -6,8 +6,8 @@

 #' 

 #' Plot a simple genome browser view. This is useful for scripted genome browser snapshots.

 #' 

-#' @param counts A \code{\link[GenomicRanges]{GRanges}} object with meta-data column 'counts'.

-#' @param peaklist A named list() of \code{\link[GenomicRanges]{GRanges}} objects containing peak coordinates.

+#' @param counts A \code{\link[GenomicRanges]{GRanges-class}} object with meta-data column 'counts'.

+#' @param peaklist A named list() of \code{\link[GenomicRanges]{GRanges-class}} objects containing peak coordinates.

 #' @param chr,start,end Chromosome, start and end coordinates for the plot.

 #' @param countcol A character giving the color for the counts.

 #' @param peakcols A character vector with colors for the peaks in \code{peaklist}.

@@ -23,15 +23,15 @@ readBamFileAsGRanges(bamfile, bamindex = bamfile, chromosomes = NULL,

 \item{max.fragment.width}{Maximum allowed fragment length. This is to filter out erroneously wrong fragments due to mapping errors of paired end reads.}

-\item{blacklist}{A \code{\link{GRanges}} or a bed(.gz) file with blacklisted regions. Reads falling into those regions will be discarded.}

+\item{blacklist}{A \code{\link{GRanges-class}} or a bed(.gz) file with blacklisted regions. Reads falling into those regions will be discarded.}

-\item{what}{A character vector of fields that are returned. Type \code{\link[Rsamtools]{scanBamWhat}} to see what is available.}

+\item{what}{A character vector of fields that are returned. Uses the \code{Rsamtools::scanBamWhat} function. See \code{\link[Rsamtools]{ScanBamParam}} to see what is available.}

 }

 \value{

-A \code{\link{GRanges}} object containing the reads.

+A \code{\link{GRanges-class}} object containing the reads.

 }

 \description{

-Import aligned reads from a BAM file into a \code{\link{GRanges}} object.

+Import aligned reads from a BAM file into a \code{\link{GRanges-class}} object.

 }

 \examples{

 ## Get an example BAM file with ChIP-seq reads

@@ -21,13 +21,13 @@ readBedFileAsGRanges(bedfile, assembly, chromosomes = NULL,

 \item{max.fragment.width}{Maximum allowed fragment length. This is to filter out erroneously wrong fragments.}

-\item{blacklist}{A \code{\link{GRanges}} or a bed(.gz) file with blacklisted regions. Reads falling into those regions will be discarded.}

+\item{blacklist}{A \code{\link{GRanges-class}} or a bed(.gz) file with blacklisted regions. Reads falling into those regions will be discarded.}

 }

 \value{

-A \code{\link{GRanges}} object containing the reads.

+A \code{\link{GRanges-class}} object containing the reads.

 }

 \description{

-Import aligned reads from a BED file into a \code{\link{GRanges}} object.

+Import aligned reads from a BED file into a \code{\link{GRanges-class}} object.

 }

 \examples{

 ## Get an example BED file with single-cell-sequencing reads

@@ -22,10 +22,10 @@ readCustomBedFile(bedfile, col.names = c("chromosome", "start", "end", "name",

 \item{sep}{Field separator from \code{\link{read.table}}.}

 }

 \value{

-A \code{\link{GRanges}} object with the contents of the bed-file.

+A \code{\link{GRanges-class}} object with the contents of the bed-file.

 }

 \description{

-This is a simple convenience function to read a bed(.gz)-file into a \code{\link{GRanges}} object. The bed-file is expected to have the following fields: \code{chromosome, start, end, name, score, strand}.

+This is a simple convenience function to read a bed(.gz)-file into a \code{\link{GRanges-class}} object. The bed-file is expected to have the following fields: \code{chromosome, start, end, name, score, strand}.

 }

 \examples{

 ## Get an example BED file

@@ -8,7 +8,7 @@ simulateMultivariate(bins, transition, emissions, weights, correlationMatrices,

   combstates, IDs, fragLen = 50)

 }

 \arguments{

-\item{bins}{A \code{\link[GenomicRanges]{GRanges}} object for which reads will be simulated.}

+\item{bins}{A \code{\link[GenomicRanges]{GRanges-class}} object for which reads will be simulated.}

 \item{transition}{A matrix with transition probabilities.}

@@ -7,12 +7,12 @@

 simulateReadsFromCounts(bins, fragLen = 50)

 }

 \arguments{

-\item{bins}{A \code{\link[GenomicRanges]{GRanges}} with read counts.}

+\item{bins}{A \code{\link[GenomicRanges]{GRanges-class}} with read counts.}

 \item{fragLen}{Length of the simulated read fragments.}

 }

 \value{

-A \code{\link[GenomicRanges]{GRanges}} with read coordinates.

+A \code{\link[GenomicRanges]{GRanges-class}} with read coordinates.

 }

 \description{

 Simulate read coordinates using read counts as input.

@@ -7,7 +7,7 @@

 simulateUnivariate(bins, transition, emission, fragLen = 50)

 }

 \arguments{

-\item{bins}{A \code{\link[GenomicRanges]{GRanges}} object for which reads will be simulated.}

+\item{bins}{A \code{\link[GenomicRanges]{GRanges-class}} object for which reads will be simulated.}

 \item{transition}{A matrix with transition probabilities.}

@@ -7,12 +7,12 @@

 subsample(binned.data, sample.reads)

 }

 \arguments{

-\item{binned.data}{A \code{\link{GRanges}} object with meta data column 'reads' that contains the read count.}

+\item{binned.data}{A \code{\link{GRanges-class}} object with meta data column 'reads' that contains the read count.}

 \item{sample.reads}{The number of reads that will be retained.}

 }

 \value{

-A \code{\link{GRanges}} object with downsampled read counts.

+A \code{\link{GRanges-class}} object with downsampled read counts.

 }

 \description{

 Normalize read counts to a given read depth. Reads counts are randomly removed from the input to match the specified read depth.

@@ -7,9 +7,9 @@

 \value{

 A \code{list()} with the following entries:

 \item{info}{Experiment table for this object.}

-\item{bincounts}{A \code{\link[GenomicRanges]{GRanges}} object containing the genomic bin coordinates and original binned read count values for different offsets.}

-\item{bins}{A \code{\link[GenomicRanges]{GRanges}} object containing the genomic bin coordinates, their read count, (optional) posteriors and state classification.}

-\item{peaks}{A \code{list()} with \code{\link[GenomicRanges]{GRanges}} containing peak coordinates for each ID in \code{info}.}

+\item{bincounts}{A \code{\link[GenomicRanges]{GRanges-class}} object containing the genomic bin coordinates and original binned read count values for different offsets.}

+\item{bins}{A \code{\link[GenomicRanges]{GRanges-class}} object containing the genomic bin coordinates, their read count, (optional) posteriors and state classification.}

+\item{peaks}{A \code{list()} with \code{\link[GenomicRanges]{GRanges-class}} containing peak coordinates for each ID in \code{info}.}

 \item{weights}{Weight for each component. Same as \code{apply(hmm$posteriors,2,mean)}.}

 \item{transitionProbs}{Matrix of transition probabilities from each state (row) into each state (column).}

 \item{transitionProbs.initial}{Initial \code{transitionProbs} at the beginning of the Baum-Welch.}

@@ -7,14 +7,14 @@

 variableWidthBins(reads, binsizes, chromosomes = NULL)

 }

 \arguments{

-\item{reads}{A \code{\link{GRanges}} with reads. See \code{\link{readBamFileAsGRanges}} and \code{\link{readBedFileAsGRanges}}.}

+\item{reads}{A \code{\link{GRanges-class}} with reads. See \code{\link{readBamFileAsGRanges}} and \code{\link{readBedFileAsGRanges}}.}

 \item{binsizes}{A vector with binsizes. Resulting bins will be close to the specified binsizes.}

 \item{chromosomes}{A subset of chromosomes for which the bins are generated.}

 }

 \value{

-A \code{list()} of \code{\link{GRanges}} objects with variable-width bins.

+A \code{list()} of \code{\link{GRanges-class}} objects with variable-width bins.

 }

 \description{

 Make variable-width bins based on a reference BAM file. This can be a simulated file (produced by TODO: insert link and aligned with your favourite aligner) or a real reference.