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),
protocolData = phenoData[,integer(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),
protocolData = phenoData[,integer(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
, annotation
, and
protocolData
.
phenoData
, featureData
, experimentData
,
annotation
, and protocolData
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-class
phenoData
:eSet
featureData
:eSet
experimentData
:eSet
annotation
:eSet
protocolData
:eSet
Class-specific methods.
as(exprSet,"ExpressionSet")
exprSet-class
to ExpressionSet
as(object,"data.frame")
ExpressionSet-class
to data.frame
by
transposing the expression matrix and concatenating phenoData
exprs(ExpressionSet)
, exprs(ExpressionSet,matrix)<-
exprs
in the AssayData-class
slot.esApply(ExpressionSet, MARGIN, FUN,
...)
ExpressionSet
objects. See esApply
.write.exprs(ExpressionSet)
write.table
Derived from eSet
:
updateObject(object, ..., verbose=FALSE)
updateObject
and eSet
isCurrent(object)
isCurrent
isVersioned(object)
isVersioned
assayData(ExpressionSet)
:eSet
sampleNames(ExpressionSet)
and sampleNames(ExpressionSet)<-
:eSet
featureNames(ExpressionSet)
, featureNames(ExpressionSet, value)<-
:eSet
dims(ExpressionSet)
:eSet
phenoData(ExpressionSet)
, phenoData(ExpressionSet,value)<-
:eSet
varLabels(ExpressionSet)
, varLabels(ExpressionSet, value)<-
:eSet
varMetadata(ExpressionSet)
, varMetadata(ExpressionSet,value)<-
:eSet
pData(ExpressionSet)
, pData(ExpressionSet,value)<-
:eSet
varMetadata(ExpressionSet)
, varMetadata(ExpressionSet,value)
eSet
experimentData(ExpressionSet)
,experimentData(ExpressionSet,value)<-
:eSet
pubMedIds(ExpressionSet)
, pubMedIds(ExpressionSet,value)
eSet
abstract(ExpressionSet)
:eSet
annotation(ExpressionSet)
, annotation(ExpressionSet,value)<-
eSet
protocolData(ExpressionSet)
, protocolData(ExpressionSet,value)<-
eSet
combine(ExpressionSet,ExpressionSet)
:eSet
storageMode(ExpressionSet)
, storageMode(ExpressionSet,character)<-
:eSet
Standard generic methods:
initialize(ExpressionSet)
:new
; not to be called directly by the user.updateObject(ExpressionSet)
:ExpressionSet
to their current definition. 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, description=paste(abstract(object), collapse="\n\n"), ...)
makeDataPackage
.as(exprSet,ExpressionSet)
:exprSet
to ExpressionSet
.as(eSet,ExpressionSet)
:eSet
portion of an object to ExpressionSet
.show(ExpressionSet)
eSet
dim(ExpressionSet)
, ncol
eSet
ExpressionSet[(index)
:eSet
ExpressionSet$
, ExpressionSet$<-
eSet
ExpressionSet[[i]]
, ExpressionSet[[i]]<-
eSet
Biocore team
eSet-class
, ExpressionSet-class
.
# create an instance of ExpressionSet new("ExpressionSet") new("ExpressionSet", exprs=matrix(runif(1000), nrow=100, ncol=10)) # update an existing ExpressionSet data(sample.ExpressionSet) updateObject(sample.ExpressionSet) # information about assay and sample data featureNames(sample.ExpressionSet)[1:10] sampleNames(sample.ExpressionSet)[1:5] phenoData(sample.ExpressionSet) experimentData(sample.ExpressionSet) # subset: first 10 genes, samples 2, 4, and 10 expressionSet <- sample.ExpressionSet[1:10,c(2,4,10)] # named features and their expression levels subset <- expressionSet[c("AFFX-BioC-3_at","AFFX-BioDn-5_at"),] exprs(subset) # samples with above-average 'score' in phenoData highScores <- expressionSet$score > mean(expressionSet$score) expressionSet[,highScores] # (automatically) coerce to data.frame lm(score~AFFX.BioDn.5_at + AFFX.BioC.3_at, data=subset)