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 the `annotation` 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)` and `sampleNames(object)<-value`:

  Coordinate accessing and setting sample names in `assayData` and `phenoData`

`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` and `colnames`; access and set feature and sample names.

`dims(object)`:

  Access the common dimensions (`dim`) or column numbers (`ncol`), or dimensions of all members (`dims`) of `assayData`.

`phenoData(object)`, `phenoData(object) <- value`:

  Access and set `phenoData`. Adding new columns to `phenoData` is often more easily done with `eSetObject[["columnName"]] <- value`.

`pData(object)`, `pData(object) <- value`:

  Access and set sample data information. Adding new columns to `pData` is often more easily done with `eSetObject[["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 the `AssayData` slot of an `eSet` instance. `assayData` returns a list or environment; elements in `assayData` not accessible in other ways (e.g., via `exprs` applied directly to the `eSet`) 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 with `eSet`. `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 set `preprocessing` information in the `MIAME-class` object associated with this `eSet`.

`combine(eSet,eSet)`:

  Combine two `eSet` objects. To be combined, eSets must have identical numbers of `featureNames`, distinct `sampleNames`, and identical `annotation`.

`storageMode(object)`, `storageMode(eSet,character)<-`:

  Change storage mode of `assayData`. Can be used to 'unlock' environments, or to change between `list` and `environment` modes of storing `assayData`.

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 of `assayData` columns

`as(eSet, "ExpressionSet")`

  Convert instance of class `"eSet"` to instance of `ExpressionSet-class`, if possible.

`as(eSet, "MultiSet")`

  Convert instance of class `"eSet"` to instance of `MultiSet-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. See `updateObjectTo`

`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`) of `assayData`.

`object[(index)`:

  Conducts subsetting of matrices and phenoData components

`object$name`, `object$name<-value`

  Access and set `name` column in `phenoData`

`object[[i, ...]]`, `object[[i, ...]]<-value`

  Access and set column `i` (character or numeric index) in `phenoData`. The ... argument can include named variables (especially `labelDescription`) to be added to varMetadata.

Additional functions:

assayDataElement(object, element)

  Return matrix `element` from `assayData` slot of `object`.

assayDataElement(object, element, validate=TRUE) <- value)

  Set element `element` in `assayData` slot of `object` to matrix `value`. If `validate=TRUE`, check that value row and column names of conform to object.

assayDataElementReplace(object, element, value, validate=TRUE)

  Set element `element` in `assayData` slot of `object` to matrix `value`. If `validate=TRUE`, check that row and column names of value conform to object.

assayDataElementNames(object)

  Return element names in `assayData` slot of `object`

`updateOldESet`

  Update versions of `eSet` constructued using `listOrEnv` as `assayData` 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")

[Package Biobase version 2.52.0 Index]