ExpressionSet {Biobase} | R Documentation

## Class to Contain and Describe High-Throughput Expression Level Assays.

### Description

Container for high-throughput assays and experimental metadata. `ExpressionSet` class is derived from `eSet`, and requires a matrix named `exprs` as assayData member.

### Usage

    ## Instance creation
    ExpressionSet(assayData,
        phenoData=annotatedDataFrameFrom(assayData, byrow=FALSE),
        featureData=annotatedDataFrameFrom(assayData, byrow=TRUE),
        experimentData=MIAME(), annotation=character(),
        protocolData=annotatedDataFrameFrom(assayData, byrow=FALSE),
        ...)

    ## Additional methods documented below

### Arguments

`assayData` | A `matrix` of expression values, or an `environment`. When `assayData` is a `matrix`, the rows represent probe sets (‘features’ in `ExpressionSet` parlance). Columns represent samples. When present, row names identify features and column names identify samples. Row and column names must be unique, and consistent with row names of `featureData` and `phenoData`, respectively. The assay data can be retrieved with `exprs()`. When `assayData` is an environment, it contains identically dimensioned matrices like that described in the previous paragraph. One of the elements of the environment must be named ‘exprs’; this element is returned with `exprs()`.
`phenoData` | An optional `AnnotatedDataFrame` containing information about each sample. The number of rows in `phenoData` must match the number of columns in `assayData`. Row names of `phenoData` must match column names of the matrix / matricies in `assayData`.
`featureData` | An optional `AnnotatedDataFrame` containing information about each feature. The number of rows in `featureData` must match the number of rows in `assayData`. Row names of `featureData` must match row names of the matrix / matricies in `assayData`.
`experimentData` | An optional `MIAME` instance with meta-data (e.g., the lab and resulting publications from the analysis) about the experiment.
`annotation` | A `character` describing the platform on which the samples were assayed. This is often the name of a Bioconductor chip annotation package, which facilitated down-stream analysis.
`protocolData` | An optional `AnnotatedDataFrame` containing equipment-generated information about protocols. The number of rows and row names of `protocolData` must agree with the dimension and column names of `assayData`.
`...` | Additional arguments, passed to `new("ExpressionSet", ...)` and available for classes that extend `ExpressionSet`.

### Extends

Directly extends class `eSet`.

### Creating Objects

`ExpressionSet` instances are usually created through `ExpressionSet()`.

### Slots

Inherited from `eSet`:

`assayData`:

  Contains matrices with equal dimensions, and with column number equal to `nrow(phenoData)`. `assayData` must contain a matrix `exprs` with rows representing features (e.g., probe sets) and columns representing samples. Additional matrices of identical size (e.g., representing measurement errors) may also be included in `assayData`. Class:`AssayData-class`

`phenoData`:

  See `eSet`

`featureData`:

  See `eSet`

`experimentData`:

  See `eSet`

`annotation`:

  See `eSet`

`protocolData`:

  See `eSet`

### Methods

Class-specific methods.

`as(exprSet,"ExpressionSet")`

  Coerce objects of `exprSet-class` to `ExpressionSet`

`as(object,"data.frame")`

  Coerce objects of `ExpressionSet-class` to `data.frame` by transposing the expression matrix and concatenating `phenoData`

`exprs(ExpressionSet)`, `exprs(ExpressionSet,matrix)<-`

  Access and set elements named `exprs` in the `AssayData-class` slot.

`esApply(ExpressionSet, MARGIN, FUN, ...)`

  'apply'-like function to conveniently operate on `ExpressionSet` objects. See `esApply`.

`write.exprs(ExpressionSet)`

  Write expression values to a text file. It takes the same arguments as `write.table`

Derived from `eSet`:

`updateObject(object, ..., verbose=FALSE)`

  Update instance to current version, if necessary. See `updateObject` and `eSet`

`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`

`assayData(ExpressionSet)`:

  See `eSet`

`sampleNames(ExpressionSet)` and `sampleNames(ExpressionSet)<-`:

  See `eSet`

`featureNames(ExpressionSet)`, `featureNames(ExpressionSet, value)<-`:

  See `eSet`

`dims(ExpressionSet)`:

  See `eSet`

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

  See `eSet`

`varLabels(ExpressionSet)`, `varLabels(ExpressionSet, value)<-`:

  See `eSet`

`varMetadata(ExpressionSet)`, `varMetadata(ExpressionSet,value)<-`:

  See `eSet`

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

  See `eSet`

`varMetadata(ExpressionSet)`, `varMetadata(ExpressionSet,value)`

  See `eSet`

`experimentData(ExpressionSet)`,`experimentData(ExpressionSet,value)<-`:

  See `eSet`

`pubMedIds(ExpressionSet)`, `pubMedIds(ExpressionSet,value)`

  See `eSet`

`abstract(ExpressionSet)`:

  See `eSet`

`annotation(ExpressionSet)`, `annotation(ExpressionSet,value)<-`

  See `eSet`

`protocolData(ExpressionSet)`, `protocolData(ExpressionSet,value)<-`

  See `eSet`

`combine(ExpressionSet,ExpressionSet)`:

  See `eSet`

`storageMode(ExpressionSet)`, `storageMode(ExpressionSet,character)<-`:

  See `eSet`

Standard generic methods:

`initialize(ExpressionSet)`:

  Object instantiation, used by `new`; not to be called directly by the user.

`updateObject(ExpressionSet)`:

  Update outdated versions of `ExpressionSet` to their current definition. See `updateObject`, `Versions-class`.

`validObject(ExpressionSet)`:

  Validity-checking method, ensuring that `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"), ...)`

  Create a data package based on an ExpressionSet object. See `makeDataPackage`.

`as(exprSet,ExpressionSet)`:

  Coerce `exprSet` to `ExpressionSet`.

`as(eSet,ExpressionSet)`:

  Coerce the `eSet` portion of an object to `ExpressionSet`.

`show(ExpressionSet)`

  See `eSet`

`dim(ExpressionSet)`, `ncol`

  See `eSet`

`ExpressionSet[(index)`:

  See `eSet`

`ExpressionSet$`, `ExpressionSet$<-`

  See `eSet`

`ExpressionSet[[i]]`, `ExpressionSet[[i]]<-`

  See `eSet`

### Author(s)

Biocore team

### See Also

`eSet-class`, `ExpressionSet-class`.

### Examples

    # create an instance of ExpressionSet
    ExpressionSet()

    ExpressionSet(assayData=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]
    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)

[Package Biobase version 2.40.0 Index]