iSet
contain one or more arrays or array-like objects with an equal number of dimensions as imageData
elements. It is assumed that the first dimension of each such element corresponds to the data features, and all other dimensions are described by associated coordinates in the pixelData
slot. Otherwise, derived classes are responsible for managing how the elements of imageData
behave and their relationship with the rows of pixelData
and featureData
. The MSImageSet
class for mass spectrometry imaging experiments is the primary derived class of iSet
. Its parent class SImageSet
is another derived class for more general images.
This class is based on the eSet
virtual class from Biobase. However, the iSet
class contains an imageData
slot which is an 'immutableEnvironment' that preserves copy-on-write behavior for iSet
derived classes, but only copying elements of imageData
when that slot specifically is modified. In addition pixelData
is an IAnnotatedDataFrame
that stores pixel information such as pixel coordinates in addition to phenotypic data.
imageData
:ImageData
, which stores one or more array or array-like objects of equal number of dimensions as elements in an 'immutableEnvironment'. This slot preserves copy-on-write behavior when it is modified specifically, but is pass-by-reference otherwise, for memory efficiency.pixelData
:IAnnotatedDataFrame
. This includes both pixel coordinates and phenotypic and sample data. Its rows correspond to individual pixels, many of which may belong to the same sample. Apart a requirement on columns describing the pixel coordinates, it is left to derived classes to decide the relationship to elements of imageData
.featureData
:imageData
.experimentData
:MIAxE
.protocolData
:pixelData
..__classVersion__
:Versions
object describing the version of the class used to created the instance. Intended for developer use.VersionedBiobase
, directly.
Versioned
, by class "VersionedBiobase", distance 2.iSet
is a virtual class. No instances can be created.sampleNames(object), sampleNames(object) <- value
:pixelData
and protocolData
slots.featureNames(object), featureNames(object) <- value
:featureData
slot.pixelNames(object), pixelNames(object) <- value
:pixelData
slot.coordLabels(object), coordLabels(object) <- value
:pixelData
slot. Note that this does not set or get coordinate names with a labelType
of sample
, regardless of whether they are currently being used to describe coordinates or not. Therefore, checking coordLabels(object)
versus names(coord(object))
is a simple way of checking whether a dataset is 2D or 3D.coord(object)
, coord(object)<-
:data.frame
containing the subset of columns of data
for which the variables have a 'labelType' of 'dim'.imageData(object), imageData(object) <- value
:imageData
slot.pixelData(object), pixelData(object) <- value
:pixelData
slot.pData(object), pData(object) <- value
:varMetadata(object), varMetadata(object) <- value
:pData
.varLabels(object), varLabels(object) <- value
:pixelData
.featureData(object), featureData(object) <- value
:featureData
slot.fData(object), fData(object) <- value
:fvarMetadata(object), fvarMetadata(object) <- value
:fData
.fvarLabels(object), fvarLabels(object) <- value
:featureData
.features(object, ...)
:featureData
) corresponding to variables in featureData
.pixels(object, ...)
:pixelData
) corresponding to variables in pixelData
.experimentData(object), experimentData(object) <-
:experimentData
slot.protocolData(object), protocolData(object) <-
:protocolData
slot.storageMode(object), storageMode(object)<-
:imageData
slot. See documentation on the storageMode
slot above for more details.initialize
:iSet
derived class. Called by new
. Not to be used by the user.validObject
:pixelData
describing the pixel coordinates, cooresponding to the dimensions of the elements of imageData
. For every named dimension of the arrays on imageData
there must be a pData
column describing its pixel coordinates. Also checks that the sampleNames
match between pixelData
and protocolData
.combine(x, y, ...)
:iSet
objects. To be combined, iSets must have identical featureData
and distinct pixelNames
and sampleNames
. All elements of imageData
must have matching names. Elements of imageData
are combined by calls for combine
.dim
:dims(object)
(which corresponds to the arrays in data
) or returned by dim(imageData(object))
. See SImageSet
for an example where this is the case, due to its use of a "virtual" datacube.dims
:data
slot.iSet$name, iSet$name <- value
:name
column in pixelData
.iSet[[i, ...]], iSet[[i, ...]] <- value
:i
(character or numeric index) in pixelData
. The ... argument can include named variables (especially 'labelDescription') to be added to the varMetadata
.eSet
,
SImageSet
,
MSImageSet
## Cannot create an iSet object
try(new("iSet"))
## Create an iSet derived class
MyImageSet <- setClass("MyImageSet", contains="iSet")
MyImageSet()
removeClass("MyImageSet")
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