BSseq-class: Class BSseq
In bsseq: Analyze, manage and store bisulfite sequencing data

Description Objects from the Class Slots Methods Utilities Coercion Assays Author(s) See Also Examples

A class for representing whole-genome or capture bisulfite sequencing data.

An object from the class links together several pieces of information. (1) genomic locations stored as a GRanges object, a location by samples matrix of M values, a location by samples matrix of Cov (coverage) values and phenodata information. In addition, there are slots for representing smoothed data. This class is an extension of RangedSummarizedExperiment.

trans:: Object of class function. This function transforms the coef slot from the scale the smoothing was done to the 0-1 methylation scale.
parameters:: Object of class list. A list of parameters representing for example how the data was smoothed.

[: signature(x = "BSseq"): Subsetting by location (using integer indices) or sample (using integers or sample names).
length: Unlike for RangedSummarizedExperiment, length() is the number of methylation loci (equal to length(granges(x))).
sampleNames,sampleNames<-: Sample names and its replacement function for the object. This is an alias for colnames.
pData,pData<-: Obtain and replace the pData slot of the phenoData slot. This is an alias for colData.
show: The show method.
combine: This function combines two BSSeq objects. The genomic locations of the new object is the union of the genomic locations of the individual objects. In addition, the methylation data matrices are placed next to each other (as appropriate wrt. the new genomic locations) and zeros are entered into the matrices as needed.

This class extends RangedSummarizedExperiment and therefore inherits a number of useful GRanges methods that operate on the rowRanges slot, used for accessing and setting the genomic locations and also do subsetByOverlaps.

There are a number of almost methods-like functions for operating on objects of class BSseq, including getBSseq, collapseBSseq, and orderBSseq. They are detailed below.

collapseBSseq(BSseq, columns)

is used to collapse an object of class BSseq. By collapsing we simply mean that certain columns (samples) are merge together by summing up the methylation evidence and coverage. This is a useful function if you start by reading in a dataset based on say flowcells and you (after QC) want to simply add a number of flowcells into one sample. The argument columns specify which samples are to be merged, in the following way: it is a character vector of new sample names, and the names of the column vector indicates which samples in the BSseq object are to be collapsed. If columns have the same length as the number of rows of BSseq (and has no names) it is assumed that the ordering corresponds to the sample ordering in BSseq.

orderBSseq(BSseq, seqOrder = NULL)

simply orders an object of class BSseq according to (increasing) genomic locations. The seqOrder vector is a character vector of seqnames(BSseq) describing the order of the chromosomes. This is useful for ordering chr1 before chr10.

chrSelectBSseq(BSseq, seqnames = NULL, order = FALSE)

subsets and optionally reorders an object of class BSseq. The seqnames vector is a character vector of seqnames(BSseq) describing which chromosomes should be retained. If order is TRUE, the chromosomes are also re-ordered using orderBSseq.

getBSseq(BSseq, type = c("Cov", "M", "gr", "coef", "se.coef", "trans", "parameters"))

is a general accessor: is used to obtain a specific slot of an object of class BSseq. It is primarily intended for internal use in the package, for users we recommend granges to get the genomic locations, getCoverage to get the coverage slots and getMeth to get the smoothed values (if they exist).

hasBeenSmoothed(BSseq)

This function returns a logical depending on whether or not the BSseq object has been smoothed using BSmooth.

combineList(list, BACKEND = NULL)

This function function is a faster way of using combine on multiple BSseq objects. The input is a list, with each component an object of class BSseq. The (slower) alternative is to use Reduce(combine, list).

The BACKEND argument determines which backend should be used for the 'M' and 'Cov' matrices and, if present, the 'coef' and 'se.coef' matrices (the latter two can only be combined if all objects have the same rowRanges). The default, BACKEND = NULL, corresponds to using matrix objects. See ?DelayedArray::setAutoRealizationBackend for alternative backends.

strandCollapse(BSseq, shift = TRUE)

This function operates on a BSseq objects which has stranded loci (i.e. loci where the strand is one of ‘+’ or ‘-’). It will collapse the methylation and coverage information across the two strands, unstranding the loci in the process and potentially re-ordering them.

The argument shift indicates whether the positions for the loci on the reverse strand should be shifted one (i.e. the positions for these loci are the positions of the ‘G’ in the ‘CpG’; this is the case for Bismark output for example).

Package versions 1.5.2 and 1.11.1 introduced a new version of representing ‘BSseq’ objects. You can update old serialized (saved) objects by invoking x <- updateObject(x).

This class overrides the default implementation of assays to make it faster. Per default, no names are added to the returned data matrices.

Assay names can conveniently be obtained by the function assayNames(x)

Kasper Daniel Hansen khansen@jhsph.edu

The package vignette. BSseq for the constructor function. RangedSummarizedExperiment for the underlying class. getBSseq, getCoverage, and getMeth for accessing the data stored in the object and finally BSmooth for smoothing the bisulfite sequence data.

M <- matrix(1:9, 3,3)
colnames(M) <- c("A1", "A2", "A3")
BStest <- BSseq(pos = 1:3, chr = c("chr1", "chr2", "chr1"), M = M, Cov = M + 2)
chrSelectBSseq(BStest, seqnames = "chr1", order = TRUE)
collapseBSseq(BStest, group = c("A", "A", "B"))

#-------------------------------------------------------------------------------
# An example using a HDF5-backed BSseq object
#
hdf5_BStest <- realize(BStest, "HDF5Array")
chrSelectBSseq(hdf5_BStest, seqnames = "chr1", order = TRUE)
collapseBSseq(
    BSseq = hdf5_BStest,
    group = c("A", "A", "B"),
    BACKEND = "HDF5Array",
    type = "integer")