BSseq {bsseq} | R Documentation

## The constructor function for BSseq objects.

### Description

The constructor function for BSseq objects.

### Usage

    BSseq(M = NULL, Cov = NULL, coef = NULL, se.coef = NULL,
      trans = NULL, parameters = NULL, pData = NULL, gr = NULL,
      pos = NULL, chr = NULL, sampleNames = NULL, rmZeroCov = FALSE)

### Arguments

`M` | A matrix-like object of methylation evidence (see 'Details' below).
`Cov` | A matrix-like object of coverage (see 'Details' below)).
`coef` | A matrix-like object of smoothing estimates (see 'Details' below).
`se.coef` | A matrix-like object of smoothing standard errors (see 'Details' below).
`trans` | A smoothing transformation.
`parameters` | A list of smoothing parameters.
`pData` | An `data.frame` or DataFrame.
`sampleNames` | A vector of sample names.
`gr` | An object of type GRanges.
`pos` | A vector of locations.
`chr` | A vector of chromosomes.
`rmZeroCov` | Should genomic locations with zero coverage in all samples be removed.

### Details

The 'M', 'Cov', 'coef', and 'se.coef' matrix-like objects will be coerced to DelayedMatrix objects; see `?DelayedArray::DelayedMatrix` for the full list of supported matrix-like objects. We recommend using matrix objects for in-memory storage of data and HDF5Matrix for on-disk storage of data.

Genomic locations are specified either through `gr` or through `chr` and `pos` but not both. There should be the same number of genomic locations as there are rows in the `M` and `Cov` matrix.

The argument `rmZeroCov` may be useful in order to reduce the size of the return object be removing methylation loci with zero coverage.

In case one or more methylation loci appears multiple times, the `M` and `Cov` matrices are summed over rows linked to the same methylation loci. See the example below.

Users should never have to specify `coef`, `se.coef`, `trans`, and `parameters`, this is for internal use (they are added by `BSmooth`).

`phenoData` is a way to specify pheno data (as known from the `ExpressionSet` and `eSet` classes), at a minimum `sampleNames` should be given (if they are not present, the function uses `col.names(M)`).

### Value

An object of class `BSseq`.

### Author(s)

Kasper Daniel Hansen khansen@jhsph.edu

### See Also

`BSseq`

### Examples

      M <- matrix(0:8, 3, 3)
      Cov <- matrix(1:9, 3, 3)
      BS1 <- BSseq(chr = c("chr1", "chr2", "chr1"), pos = c(1,2,3),
                   M = M, Cov = Cov, sampleNames = c("A","B", "C"))
      BS1
      BS2 <- BSseq(chr = c("chr1", "chr1", "chr1"), pos = c(1,1,1),
                   M = M, Cov = Cov, sampleNames = c("A","B", "C"))
      BS2

      #-------------------------------------------------------------------------------
      # An example using a HDF5Array-backed BSseq object
      #

      library(HDF5Array)
      hdf5_M <- realize(M, "HDF5Array")
      hdf5_Cov <- realize(Cov, "HDF5Array")
      hdf5_BS1 <- BSseq(chr = c("chr1", "chr2", "chr1"),
                        pos = c(1, 2, 3),
                        M = hdf5_M,
                        Cov = hdf5_Cov,
                        sampleNames = c("A", "B", "C"))
      hdf5_BS1
      hdf5_BS2 <- BSseq(chr = c("chr1", "chr1", "chr1"),
                        pos = c(1, 1, 1),
                        M = hdf5_M,
                        Cov = hdf5_Cov,
                        sampleNames = c("A", "B", "C"))
      hdf5_BS2

[Package bsseq version 1.18.0 Index]