DBAmmd-Accessors: Extract data from DBAmmd objects
In MMDiff2: Statistical Testing for ChIP-Seq data sets

Description Usage Arguments Value See Also Examples

This help file describes different ways to access the slots and values contained in a DBAmmd-class objects.

## S4 method for signature 'DBAmmd'
Genome(x)

## S4 method for signature 'DBAmmd'
Samples(x)

## S4 method for signature 'DBAmmd'
numPeaks(x)

## S4 method for signature 'DBAmmd'
numSamples(x)

## S4 method for signature 'DBAmmd'
metaData(x)

## S4 method for signature 'DBAmmd'
Regions(x)

## S4 method for signature 'DBAmmd'
Reads(x, whichPos = "Center")

## S4 method for signature 'DBAmmd'
Counts(x, whichCounts = "T")

## S4 method for signature 'DBAmmd'
Hists(x, whichPos = "Center")

## S4 method for signature 'DBAmmd'
Dists(x, dist.method = NULL)

## S4 method for signature 'DBAmmd'
Contrast(x, whichContrast = 1)

## S4 method for signature 'DBAmmd'
setRegions(x, Regions)

## S4 method for signature 'DBAmmd'
setContrast(x, contrast)

`x`	a DBAmmd Object. An empty instance can be created using `DBAmmd()`. (See `DBAmmd-class` for more details.)
`whichPos`	specifies which relative positions of mapped fragments should to be considered. Can be one of: 'Left.p', 'Right.p', 'Right.p' and 'Left.n': Start and end positions of fragments mapping to positive or negative strand, respectively ('Right.p' and 'Left.n' are not available for single-end reads). Additionally inferred positions: 'Center.n','Center.p','Center','Left','Right'. (DEFAULT: 'Center')
`whichCounts`	can be 'T': total counts, or 'p','n': counts of reads mapping to positive, negative strand, respectively.
`dist.method`	specify method used for distances between samples. Currently only Maximum Mean Discrepancy (MMD) and Kolmogorov-Smirnov (KS) implemented. (DEFAULT: 'MMD')
`whichContrast`	index determining which of the set contrast should be used. (DEFAULT: 1)
`Regions`	GRanges Object specifying the Regions of Interesst / Peaks.
`contrast`	determines how to set a new contrast for differential analysis. A contrast can be automatically created either 'byCondition', or 'byTissue'. The Contrast can also be manually set (see vignette for details).

Genome(x) returns the name of the used genome version, if set in the metaData.

Samples(x) returns the information which was provided in the SampleSheet.csv to describe the data.

numPeaks(x) returns the number of Peaks / Regions of Interest that are associated with the DBAmmd object.

numSamples(x) returns the number of samples associated with the DBAmmd object.

metaData(x) returns the metaData associated with the DBAmmd object.

Regions(x) returns the Peaks / Regions of Interest that are associated with the DBAmmd object.

Reads(x,whichPos) returns the Reads mapping to the Regions of Interest.

Counts(x,whichCounts) returns a m x n matrix containing the Counts of Reads mapping to the Peaks / Regions of Interest. Depending on the value of 'whichCounts', total counts ('T'), or counts of reads mapping to positive ('p'), or negative strand ('n') are returnt. See getPeakReads for more details.

Hists(x,whichPos) returns a list of matrices of length m (number of Peaks). Each matrix is a n x L_i matrix, where n is the number of samples and L_i is the number of bins used to cover the extend of the peak. Note, L_i varies between peaks of different lengths. See compHists for more details.

Dists(x,dist.method) returns a matrix containing distances between pairs of samples for each peak. See compDists for more details.

Contrast(x,whichContrast) returns the specified contrast.

setRegions(x,Regions) returns a DBAmmd Object with set Peaks / Regions of Interests.

setContrast(x,contrast) returns a DBAmmd Object with a set contrast.

DBAmmd-class

data("MMD")

Samples(MMD)
Genome(MMD)
numPeaks(MMD)
numSamples(MMD)
metaData(MMD)
R <- Regions(MMD)
Pos <- Reads(MMD)
C <- Counts(MMD)
H <- Hists(MMD)
D <- Dists(MMD)
C1 <- Contrast(MMD)