AnnotatedDataFrame {Biobase} | R Documentation

## Class Containing Measured Variables and Their Meta-Data Description.

### Description

An `AnnotatedDataFrame` consists of two parts. There is a collection of samples and the values of variables measured on those samples. There is also a description of each variable measured. The components of an `AnnotatedDataFrame` can be accessed with `pData` and `varMetadata`.

### Extends

Versioned

### Creating Objects

`new("AnnotatedDataFrame")`

`new("AnnotatedDataFrame", data=data.frame(), varMetadata=data.frame(), dimLabels=c("rowNames", "columnNames"))`

`AnnotatedDataFrame` instances are created using `new`. The initialize method takes up to three arguments, `data`, `varMetadata`, and `dimLabels`. `data` is a `data.frame` of the samples (rows) and measured variables (columns). `varMetadata` is a `data.frame` with the number of rows equal to the number of columns of the `data` argument. `varMetadata` describes aspects of each measured variable. `dimLabels` provides aesthetic control for labeling rows and columns in the `show` method. `varMetadata` and `dimLabels` can be missing.

`as(data.frame, "AnnotatedDataFrame")` coerces a `data.frame` to an `AnnotatedDataFrame`.

`annotatedDataFrameFrom` may be a convenient way to create an `AnnotatedDataFrame` from `AssayData-class`.

### Slots

Class-specific slots:

`data`:
  A `data.frame` containing samples (rows) and measured variables (columns).
`varMetadata`:
  A `data.frame` with number of rows equal number of columns in `data`, and at least one column, named `labelDescription`, containing a textual description of each variable.

### Methods

Class-specific methods.

`combine(<AnnotatedDataFrame>, <AnnotatedDataFrame>`:
  Bind data from one `AnnotatedDataFrame` to a second `AnnotatedDataFrame`, returning the result as an `AnnotatedDataFrame`. Row (sample) names in each argument must be unique. Variable names present in both arguments occupy a single column in the resulting `AnnotatedDataFrame`. Variable names unique to either argument create columns with values assigned for those samples where the variable is present. `varMetadata` in the returned `AnnotatedDataFrame` is updated to reflect the combination.
`pData(<AnnotatedDataFrame>)`, `pData(<AnnotatedDataFrame>)<-<data.frame>`:
  Set and retrieve the data (samples and variables) in the `AnnotatedDataFrame`
`varMetadata(<AnnotatedDataFrame>)`, `varMetadata(<AnnotatedDataFrame>)<-<data.frame>`:
  Set and retrieve the meta-data (variables and their descriptions) in the `AnnotatedDataFrame`
`featureNames(<AnnotatedDataFrame>)`, `featureNames(<AnnotatedDataFrame>)<-<ANY>`:
  Set and retrieve the feature names in `AnnotatedDataFrame`; a synonym for `sampleNames`.
`sampleNames(<AnnotatedDataFrame>)`, `sampleNames(<AnnotatedDataFrame>)<-<ANY>`:
  Set and retrieve the sample names in `AnnotatedDataFrame`
`varLabels(<AnnotatedDataFrame>)`, `varLabels(<AnnotatedDataFrame>)<-<data.frame>`:
  Set and retrieve the variable labels in the `AnnotatedDataFrame`
`dimLabels(<AnnotatedDataFrame>)`, `dimLabels(<AnnotatedDataFrame>) <- <character>`
  Retrieve labels used for display of `AnnotatedDataFrame`, e.g., ‘rowNames’, ‘columnNames’.

Standard generic methods:

`initialize(<AnnotatedDataFrame>)`:
  Object instantiation, used by `new`; not to be called directly by the user.
`as(<data.frame>, "AnnotatedDataFrame")`:
  Convert a `data.frame` to an AnnotatedDataFrame.
`as(<phenoData>,<AnnotatedDataFrame>)`:
  Convert old-style `phenoData-class` objects to `AnnotatedDataFrame`, issuing warnings as appropriate.
`validObject(<AnnotatedDataFrame>)`:
  Validity-checking method, ensuring coordination between `data` and `varMetadata` elements
`updateObject(object, ..., verbose=FALSE)`
  Update instance to current version, if necessary. See `updateObject`
`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(<AnnotatedDataFrame>)`
  Abbreviated display of object
`[<sample>,<variable>`:
  Subset operation, taking two arguments and indexing the sample and variable. Returns an `AnnotatedDataFrame`, i.e., including relevant metadata. Unlike a `data.frame`, setting `drop=TRUE` generates an error.
`[[<variable>`, `$<variable>`:
  Selector returning a variable (column of `pData`).
`[[<variable>, ...]]<-<new_value>`, `$<variable> <- <new_value>`:
  Replace or add a variable to `pData`. ... can include named arguments (especially `labelDescription`) to be added to `varMetadata`.
`dim(<AnnotatedDataFrame>)`, `ncol(<AnnotatedDataFrame>)`:
  Number of samples and variables (`dim`) and variables (`ncol`) in the argument.

### Author(s)

V.J. Carey, after initial design by R. Gentleman

### See Also

`eSet`, `ExpressionSet`, `read.AnnotatedDataFrame`

### Examples

    df <- data.frame(x=1:6,
                     y=rep(c("Low", "High"),3),
                     z=I(LETTERS[1:6]),
                     row.names=paste("Sample", 1:6, sep="_"))
    metaData <-
      data.frame(labelDescription=c(
                   "Numbers",
                   "Factor levels",
                   "Characters"))

    new("AnnotatedDataFrame")
    new("AnnotatedDataFrame", data=df)
    new("AnnotatedDataFrame",
        data=df, varMetadata=metaData)

    as(df, "AnnotatedDataFrame")

    obj <- new("AnnotatedDataFrame")
    pData(obj) <- df
    varMetadata(obj) <- metaData
    validObject(obj)

[Package Biobase version 2.0.1 Index]