| ExpressionSet {Biobase} | R Documentation |
Container for high-throughput assays and experimental
metadata. ExpressionSet class is derived from
eSet, and requires a matrix named exprs as
assayData member.
Directly extends class eSet.
new("ExpressionSet")
new("ExpressionSet",
phenoData = new("AnnotatedDataFrame"),
featureData = new("AnnotatedDataFrame"),
experimentData = new("MIAME"),
annotation = character(0),
exprs = new("matrix"))
This creates an ExpressionSet with assayData implicitly
created to contain exprs. Additional named matrix arguments
with the same dimensions as exprs are added to
assayData; the row and column names of these additional
matricies should match those of exprs.
new("ExpressionSet",
assayData = assayDataNew(exprs=new("matrix")),
phenoData = new("AnnotatedDataFrame"),
featureData = new("AnnotatedDataFrame"),
experimentData = new("MIAME"),
annotation = character(0))
This creates an ExpressionSet with assayData provided
explicitly. In this form, the only required named argument is
assayData.
as([exprSet],"ExpressionSet")
ExpressionSet instances are usually created through
new("ExpressionSet", ...). Usually the arguments to new
include exprs (a matrix of expression data, with features
corresponding to rows and samples to columns), phenoData, featureData,
experimentData, and annotation.
phenoData, featureData, experimentData, and annotation can be
missing, in which case they are assigned default values.
Inherited from eSet:
assayData:nrow(phenoData). assayData must contain a matrix
exprs with rows represening features (e.g., reporters)
and columns representing samples. Additional matrices of
identical size (e.g., representing measurement errors) may
also be included in assayData. Class:AssayData-classphenoData:eSetfeatureData:eSetexperimentData:eSetannotation:eSetClass-specific methods.
as(exprSet,"ExpressionSet")exprSet-class to ExpressionSetas(object,"data.frame")ExpressionSet-class to data.frame by
transposing the expression matrix and concatenating phenoDataexprs(ExpressionSet), exprs(ExpressionSet,matrix)<-exprs in the AssayData-class
slot.write.exprs(ExpressionSet)write.table
Derived from eSet:
updateObject(object, ..., verbose=FALSE)updateObject and eSetisCurrent(object)isCurrentisVersioned(object)isVersionedsampleNames(ExpressionSet) and sampleNames(ExpressionSet)<-:eSetfeatureNames(ExpressionSet), featureNames(ExpressionSet, value)<-:eSetgeneNames(ExpressionSet) and
geneNames(ExpressionSet, value)<-:featureNames which is the preferred
accessor of expression matrix row names.dims(ExpressionSet):eSetphenoData(ExpressionSet), phenoData(ExpressionSet,value)<-:eSetvarLabels(ExpressionSet), varLabels(ExpressionSet, value)<-:eSetvarMetadata(ExpressionSet), varMetadata(ExpressionSet,value)<-:eSetpData(ExpressionSet), pData(ExpressionSet,value)<-:eSetvarMetadata(ExpressionSet), varMetadata(ExpressionSet,value)eSetexperimentData(ExpressionSet),experimentData(ExpressionSet,value)<-:eSetpubMedIds(ExpressionSet), pubMedIds(ExpressionSet,value)eSetabstract(ExpressionSet):eSetannotation(ExpressionSet), annotation(ExpressionSet,value)<-eSetcombine(ExpressionSet,ExpressionSet):eSetstorageMode(ExpressionSet), storageMode(ExpressionSet,character)<-:eSetreporterNames(ExpressionSet), reporterNames(ExpressionSet,value)<-:Standard generic methods:
initialize(ExpressionSet):new; not to be called directly by the user.updateObject(ExpressionSet):ExpressionSet to their current definiton. See
updateObject, Versions-class.validObject(ExpressionSet):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,
...)makeDataPackage.as(exprSet,ExpressionSet):exprSet too ExpressionSet.as(eSet,ExpressionSet):eSet portion of an object to ExpressionSet.show(ExpressionSet)eSetdim(ExpressionSet), ncoleSetExpressionSet[(index):eSetExpressionSet$, ExpressionSet$<-eSetExpressionSet[[i]], ExpressionSet[[i]]<-eSetBiocore team
eSet-class, ExpressionSet-class.
# create an instance of ExpressionSet
new("ExpressionSet")
new("ExpressionSet",
exprs=matrix(runif(1000), nrow=100, ncol=10))
# update an existing ExpressionSet
data(sample.ExpressionSet)
updateObject(sample.ExpressionSet)
# update existing exprSet-like class to ExpressionSet
data(sample.exprSet)
expressionSet <- as(sample.exprSet,"ExpressionSet")
expressionSet
# information about assay and sample data
featureNames(expressionSet)[1:10]
sampleNames(expressionSet)[1:5]
phenoData(expressionSet)
experimentData(expressionSet)
# subset: first 10 genes, samples 2, 4, and 10
expressionSet <- as(sample.exprSet,"ExpressionSet")
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)