SeqCountSet-class: Class '"SeqCountSet"' - container for count data from...

In haowulab/DSS: Dispersion shrinkage for sequencing data

Class "SeqCountSet" - container for count data from sequencing experiment

Description

This class is the main container for storing *RNA-seq* data. It is directly inherited fro 'ExpressionSet' class, with two more fields 'normalizationFactor' for normalization factors and 'dispersion' for gene-wise dispersions.

The class for BS-seq data is *BSseq*, which is imported from bsseq package.

Slots

normalizationFactor:

Normalization factor for counts.

dispersion:

Gene-wise dispersions.

experimentData:

See 'ExpressionSet'.

assayData:

See 'ExpressionSet'.

phenoData:

See 'ExpressionSet'.

featureData:

See 'ExpressionSet'.

annotation:

See 'ExpressionSet'.

protocolData:

See 'ExpressionSet'.

Extends

Class "ExpressionSet", directly. Class "eSet", by class "ExpressionSet", distance 2. Class "VersionedBiobase", by class "ExpressionSet", distance 3. Class "Versioned", by class "ExpressionSet", distance 4.

Constructor

newSeqCountSet(counts, designs,normalizationFactor,featureData): Creates a 'SeqCountSet' object.

counts

A matrix of integers with rows corresponding to genes and columns for samples.

designs

A vector or data frame representing experimental design. The length of the vector or number of rows of the data frame must match the number of columns of input counts. This field can be accessed using 'pData' function.

normalizationFactor

A vector or matrix of normalization factors for the counts.

featureData

Additional information for genes as an 'AnnotatedDataFrame' object. This field can be access by using 'featureData' function.

Methods

dispersion, dispersion<- :

Access and set gene-wise dispersions.

normalizationFactor, normalizationFactor<- :

Access and set normalization factors.

Note

This is similar to 'CountDataSet' in DESeq or 'DGEList' in edgeR.

Author(s)

Hao Wu <[e-mail]>

See Also

dispersion, normalizationFactor

Examples

## simulate data from RNA-seq
counts=matrix(rpois(600, 10), ncol=6)
designs=c(0,0,0,1,1,1)
seqData=newSeqCountSet(counts, designs)
seqData
pData(seqData)
head(exprs(seqData))

## multiple factor designs
design=data.frame(gender=c(rep("M",4), rep("F",4)), strain=rep(c("WT", "Mutant"),4))
X=model.matrix(~gender+strain, data=design)
counts=matrix(rpois(800, 10), ncol=8)
seqData=newSeqCountSet(counts, as.data.frame(X))
seqData
pData(seqData)

haowulab/DSS documentation built on Oct. 28, 2023, 6:59 p.m.