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 matricies 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 useage.

### Creating Objects

`eSet` is a virtual class, so instances cannot be created.

Objects created under previous definitions of `eSet-class` can be coerced to classes derived based on `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 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`
`.classVersion`:
  Character vector describing the R and Biobase version number used to created the instance. Intended for developer use. Class: `Versions-class`

### 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`.
`dims(object)`:
  Access the common dimensions (`dim`) or column numbers (`ncol`), or dimensions of all memebers (`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.
`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) <- value)
  Set element `element` in `assayData` slot of `object` to matrix `value`
assayDataElementReplace(object, element, value)
  Set element `element` in `assayData` slot of `object` to matrix `value`
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
    setClass("MySet", contains="eSet")
    new("MySet")

    # Create a more robust class, with initialization and validation methods
    # to ensure assayData contains specific matricies
    setClass("TwoColorSet", contains="eSet")

    setMethod("initialize", "TwoColorSet",
              function(.Object,
                       phenoData = new("AnnotatedDataFrame"),
                       experimentData = new("MIAME"),
                       annotation = character(),
                       R = new("matrix"),
                       G = new("matrix"),
                       Rb = new("matrix"),
                       Gb = new("matrix"),
                       ... ) {
                callNextMethod(.Object,
                               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"))
    })

    new("TwoColorSet")

    # eSet objects cannot be instantiated directly, only derived objects
    try(new("eSet"))

    removeClass("MySet")
    removeClass("TwoColorSet")
    removeMethod("initialize", "TwoColorSet")

[Package Biobase version 2.0.1 Index]