eSet {Biobase} | R Documentation |
Class to Contain High-Throughput Assays and Experimental Metadata
Description
Container for high-throughput assays and experimental
metadata. Classes derived from eSet
contain one or more
identical-sized matrices as assayData
elements. Derived
classes (e.g., ExpressionSet-class
, SnpSet-class
)
specify which elements must be present in the assayData
slot.
eSet
object cannot be instantiated directly; see the examples
for usage.
Creating Objects
eSet
is a virtual class, so instances cannot be created.
Objects created under previous definitions of eSet-class
can be
coerced to the current classes derived from eSet
using
updateOldESet
.
Slots
Introduced in eSet
:
assayData
:Contains matrices with equal dimensions, and with column number equal to
nrow(phenoData)
. Class:AssayData-class
phenoData
:Contains experimenter-supplied variables describing sample (i.e., columns in
assayData
) phenotypes. Class:AnnotatedDataFrame-class
featureData
:Contains variables describing features (i.e., rows in
assayData
) unique to this experiment. Use theannotation
slot to efficiently reference feature data common to the annotation package used in the experiment. Class:AnnotatedDataFrame-class
experimentData
:Contains details of experimental methods. Class:
MIAME-class
annotation
:Label associated with the annotation package used in the experiment. Class:
character
protocolData
:Contains microarray equipment-generated variables describing sample (i.e., columns in
assayData
) phenotypes. Class:AnnotatedDataFrame-class
.__classVersion__
:A
Versions
object describing the R and Biobase version numbers used to created the instance. Intended for developer use.
Methods
Methods defined in derived classes (e.g., ExpressionSet-class
,
SnpSet-class
) may override the methods described here.
Class-specific methods:
sampleNames(object)
andsampleNames(object)<-value
:Coordinate accessing and setting sample names in
assayData
andphenoData
featureNames(object)
,featureNames(object) <- value
:Coordinate accessing and setting of feature names (e.g, genes, probes) in
assayData
.dimnames(object)
,dimnames(object) <- value
:Also
rownames
andcolnames
; access and set feature and sample names.dims(object)
:Access the common dimensions (
dim
) or column numbers (ncol
), or dimensions of all members (dims
) ofassayData
.phenoData(object)
,phenoData(object) <- value
:Access and set
phenoData
. Adding new columns tophenoData
is often more easily done witheSetObject[["columnName"]] <- value
.pData(object)
,pData(object) <- value
:Access and set sample data information. Adding new columns to
pData
is often more easily done witheSetObject[["columnName"]] <- value
.varMetadata(object)
,varMetadata(eSet,value)
Access and set metadata describing variables reported in
pData
varLabels(object)
,varLabels(eSet, value)<-
:Access and set variable labels in
phenoData
.featureData(object)
,featureData(object) <- value
:Access and set
featureData
.fData(object)
,fData(object) <- value
:Access and set feature data information.
fvarMetadata(object)
,fvarMetadata(eSet,value)
Access and set metadata describing features reported in
fData
fvarLabels(object)
,fvarLabels(eSet, value)<-
:Access and set variable labels in
featureData
.assayData(object), assayData(object) <- value
:-
signature(object = "eSet", value = "AssayData")
: Access and replace theAssayData
slot of aneSet
instance.assayData
returns a list or environment; elements inassayData
not accessible in other ways (e.g., viaexprs
applied directly to theeSet
) can most reliably be accessed with, e.g.,assayData(obj)[["se.exprs"]]
. experimentData(object)
,experimentData(object) <- value
:Access and set details of experimental methods
description(object)
,description(object) <- value
:Synonymous with experimentData.
notes(object)
,notes(object) <- value
:-
signature(object="eSet", value="list")
Retrieve and set unstructured notes associated witheSet
.signature(object="eSet", value="character")
As with value="list", but append value to current list of notes. pubMedIds(object)
,pubMedIds(eSet,value)
Access and set PMIDs in
experimentData
.abstract(object)
:Access abstract in
experimentData
.annotation(object)
,annotation(object) <- value
Access and set annotation label indicating package used in the experiment.
protocolData(object)
,protocolData(object) <- value
Access and set the protocol data.
preproc(object)
,preproc(object) <- value
:signature(object="eSet", value="list")
Access and setpreprocessing
information in theMIAME-class
object associated with thiseSet
.combine(eSet,eSet)
:Combine two
eSet
objects. To be combined, eSets must have identical numbers offeatureNames
, distinctsampleNames
, and identicalannotation
.storageMode(object)
,storageMode(eSet,character)<-
:Change storage mode of
assayData
. Can be used to 'unlock' environments, or to change betweenlist
andenvironment
modes of storingassayData
.
Standard generic methods:
initialize(object)
:Object instantiation, can be called by derived classes but not usually by the user.
validObject(object)
:Validity-checking method, ensuring (1) all assayData components have the same number of features and samples; (2) the number and names of
phenoData
rows match the number and names ofassayData
columnsas(eSet, "ExpressionSet")
Convert instance of class
"eSet"
to instance ofExpressionSet-class
, if possible.as(eSet, "MultiSet")
Convert instance of class
"eSet"
to instance ofMultiSet-class
, if possible.updateObject(object, ..., verbose=FALSE)
Update instance to current version, if necessary. Usually called through class inheritance rather than directly by the user. See
updateObject
updateObjectTo(object, template, ..., verbose=FALSE)
Update instance to current version by updating slots in
template
, if necessary. Usually call by class inheritance, rather than directly by the user. SeeupdateObjectTo
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
show(object)
Informatively display object contents.
dim(object)
,ncol
Access the common dimensions (
dim
) or column numbers (ncol
), of all memebers (dims
) ofassayData
.object[(index)
:Conducts subsetting of matrices and phenoData components
object$name
,object$name<-value
Access and set
name
column inphenoData
object[[i, ...]]
,object[[i, ...]]<-value
Access and set column
i
(character or numeric index) inphenoData
. The ... argument can include named variables (especiallylabelDescription
) to be added to varMetadata.
Additional functions:
- assayDataElement(object, element)
Return matrix
element
fromassayData
slot ofobject
.- assayDataElement(object, element, validate=TRUE) <- value)
Set element
element
inassayData
slot ofobject
to matrixvalue
. Ifvalidate=TRUE
, check that value row and column names of conform to object.- assayDataElementReplace(object, element, value, validate=TRUE)
Set element
element
inassayData
slot ofobject
to matrixvalue
. Ifvalidate=TRUE
, check that row and column names of value conform to object.- assayDataElementNames(object)
Return element names in
assayData
slot ofobject
updateOldESet
Update versions of
eSet
constructued usinglistOrEnv
asassayData
slot (before May, 2006).
Author(s)
Biocore team
See Also
Method use in ExpressionSet-class
.
Related classes
AssayData-class
, AnnotatedDataFrame-class
, MIAME-class
.
Derived classes
ExpressionSet-class
, SnpSet-class
.
To update objects from previous class versions, see updateOldESet
.
Examples
# update previous eSet-like class oldESet to existing derived class
## Not run: updateOldESet(oldESet, "ExpressionSet")
# create a new, ad hoc, class, for personal use
# all methods outlined above are available automatically
.MySet <- setClass("MySet", contains="eSet")
.MySet()
# Create a more robust class, with constructor and validation methods
# to ensure assayData contains specific matricies
.TwoColorSet <- setClass("TwoColorSet", contains="eSet")
TwoColorSet <-
function(phenoData=AnnotatedDataFrame(), experimentData=MIAME(),
annotation=character(), R=new("matrix"), G=new("matrix"),
Rb=new("matrix"), Gb=new("matrix"), ...)
{
.TwoColorSet(phenoData=phenoData, experimentData=experimentData,
annotation=annotation, R=R, G=G, Rb=Rb, Gb=Gb, ...)
}
setValidity("TwoColorSet", function(object) {
assayDataValidMembers(assayData(object), c("R", "G", "Rb", "Gb"))
})
TwoColorSet()
# eSet objects cannot be instantiated directly, only derived objects
try(new("eSet"))
removeClass("MySet")
removeClass("TwoColorSet")