Biobase: class.ExpressionSet – R documentation

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class.ExpressionSet

Class to Contain and Describe High-Throughput Expression Level Assays.

Description

Container for high-throughput assays and experimental metadata. ExpressionSet class is derived from eSet, and requires a matrix named exprs as assayData member.

Usage

## Instance creation
ExpressionSet(assayData,
    phenoData=annotatedDataFrameFrom(assayData, byrow=FALSE),
    featureData=annotatedDataFrameFrom(assayData, byrow=TRUE),
    experimentData=MIAME(), annotation=character(),
    protocolData=annotatedDataFrameFrom(assayData, byrow=FALSE),
    ...)

## Additional methods documented below

Arguments

`assayData`	A `matrix` of expression values, or an `environment`. When `assayData` is a `matrix`, the rows represent probe sets (‘features’ in `ExpressionSet` parlance). Columns represent samples. When present, row names identify features and column names identify samples. Row and column names must be unique, and consistent with row names of `featureData` and `phenoData`, respectively. The assay data can be retrieved with `exprs()`. When `assayData` is an environment, it contains identically dimensioned matrices like that described in the previous paragraph. One of the elements of the environment must be named ‘exprs’; this element is returned with `exprs()`.
`phenoData`	An optional `AnnotatedDataFrame` containing information about each sample. The number of rows in `phenoData` must match the number of columns in `assayData`. Row names of `phenoData` must match column names of the matrix / matricies in `assayData`.
`featureData`	An optional `AnnotatedDataFrame` containing information about each feature. The number of rows in `featureData` must match the number of rows in `assayData`. Row names of `featureData` must match row names of the matrix / matricies in `assayData`.
`experimentData`	An optional `MIAME` instance with meta-data (e.g., the lab and resulting publications from the analysis) about the experiment.
`annotation`	A `character` describing the platform on which the samples were assayed. This is often the name of a Bioconductor chip annotation package, which facilitated down-stream analysis.
`protocolData`	An optional `AnnotatedDataFrame` containing equipment-generated information about protocols. The number of rows and row names of `protocolData` must agree with the dimension and column names of `assayData`.
`...`	Additional arguments, passed to `new("ExpressionSet", ...)` and available for classes that extend `ExpressionSet`.

Extends

Directly extends class eSet.

Creating Objects

ExpressionSet instances are usually created through ExpressionSet().

Slots

Inherited from eSet:

assayData:: Contains matrices with equal dimensions, and with column number equal to nrow(phenoData). assayData must contain a matrix exprs with rows representing features (e.g., probe sets) and columns representing samples. Additional matrices of identical size (e.g., representing measurement errors) may also be included in assayData. Class:AssayData-class
phenoData:: See eSet
featureData:: See eSet
experimentData:: See eSet
annotation:: See eSet
protocolData:: See eSet

Methods

Class-specific methods.

as(exprSet,"ExpressionSet"): Coerce objects of exprSet-class to ExpressionSet
as(object,"data.frame"): Coerce objects of ExpressionSet-class to data.frame by transposing the expression matrix and concatenating phenoData
exprs(ExpressionSet), exprs(ExpressionSet,matrix)<-: Access and set elements named exprs in the AssayData-class slot.
esApply(ExpressionSet, MARGIN, FUN, ...): 'apply'-like function to conveniently operate on ExpressionSet objects. See esApply.
write.exprs(ExpressionSet): Write expression values to a text file. It takes the same arguments as write.table

Derived from eSet:

updateObject(object, ..., verbose=FALSE): Update instance to current version, if necessary. See updateObject and eSet
isCurrent(object): Determine whether version of object is current. See isCurrent
isVersioned(object): Determine whether object contains a 'version' string describing its structure . See isVersioned
assayData(ExpressionSet):: See eSet
sampleNames(ExpressionSet) and sampleNames(ExpressionSet)<-:: See eSet
featureNames(ExpressionSet), featureNames(ExpressionSet, value)<-:: See eSet
dims(ExpressionSet):: See eSet
phenoData(ExpressionSet), phenoData(ExpressionSet,value)<-:: See eSet
varLabels(ExpressionSet), varLabels(ExpressionSet, value)<-:: See eSet
varMetadata(ExpressionSet), varMetadata(ExpressionSet,value)<-:: See eSet
pData(ExpressionSet), pData(ExpressionSet,value)<-:: See eSet
varMetadata(ExpressionSet), varMetadata(ExpressionSet,value): See eSet
experimentData(ExpressionSet),experimentData(ExpressionSet,value)<-:: See eSet
pubMedIds(ExpressionSet), pubMedIds(ExpressionSet,value): See eSet
abstract(ExpressionSet):: See eSet
annotation(ExpressionSet), annotation(ExpressionSet,value)<-: See eSet
protocolData(ExpressionSet), protocolData(ExpressionSet,value)<-: See eSet
combine(ExpressionSet,ExpressionSet):: See eSet
storageMode(ExpressionSet), storageMode(ExpressionSet,character)<-:: See eSet

Standard generic methods:

initialize(ExpressionSet):: Object instantiation, used by new; not to be called directly by the user.
updateObject(ExpressionSet):: Update outdated versions of ExpressionSet to their current definition. See updateObject, Versions-class.
validObject(ExpressionSet):: Validity-checking method, ensuring that exprs is a member of assayData. checkValidity(ExpressionSet) imposes this validity check, and the validity checks of eSet.
makeDataPackage(object, author, email, packageName, packageVersion, license, biocViews, filePath, description=paste(abstract(object), collapse="\n\n"), ...): Create a data package based on an ExpressionSet object. See makeDataPackage.
as(exprSet,ExpressionSet):: Coerce exprSet to ExpressionSet.
as(eSet,ExpressionSet):: Coerce the eSet portion of an object to ExpressionSet.
show(ExpressionSet): See eSet
dim(ExpressionSet), ncol: See eSet
ExpressionSet[(index):: See eSet
ExpressionSet$, ExpressionSet$<-: See eSet
ExpressionSet[[i]], ExpressionSet[[i]]<-: See eSet

Author(s)

Biocore team

Examples

# create an instance of ExpressionSet
ExpressionSet()

ExpressionSet(assayData=matrix(runif(1000), nrow=100, ncol=10))

# update an existing ExpressionSet
data(sample.ExpressionSet)
updateObject(sample.ExpressionSet)

# information about assay and sample data
featureNames(sample.ExpressionSet)[1:10]
sampleNames(sample.ExpressionSet)[1:5]
experimentData(sample.ExpressionSet)

# subset: first 10 genes, samples 2, 4, and 10
expressionSet <- sample.ExpressionSet[1:10,c(2,4,10)]

# named features and their expression levels
subset <- expressionSet[c("AFFX-BioC-3_at","AFFX-BioDn-5_at"),]
exprs(subset)

# samples with above-average 'score' in phenoData
highScores <- expressionSet$score > mean(expressionSet$score)
expressionSet[,highScores]

# (automatically) coerce to data.frame
lm(score~AFFX.BioDn.5_at + AFFX.BioC.3_at, data=subset)

Biobase

Biobase: Base functions for Bioconductor

v2.50.0

Artistic-2.0

Authors

R. Gentleman, V. Carey, M. Morgan, S. Falcon

Initial release