MultiAssayExperiment {MultiAssayExperiment} | R Documentation

## Construct an integrative representation of multi-omic data with `MultiAssayExperiment`

### Description

The constructor function for the MultiAssayExperiment-class combines multiple data elements from the different hierarchies of data (study, experiments, and samples). It can create instances where neither a `sampleMap` or a `colData` set is provided. Please see the MultiAssayExperiment API documentation for more information.

### Usage

    MultiAssayExperiment(
      experiments = ExperimentList(),
      colData = S4Vectors::DataFrame(),
      sampleMap = S4Vectors::DataFrame(assay = factor(), primary = character(), colname =
        character()),
      metadata = list(),
      drops = list()
    )

### Arguments

`experiments` | A `list` or ExperimentList of all combined experiments
`colData` | A `DataFrame` or `data.frame` of characteristics for all biological units
`sampleMap` | A `DataFrame` or `data.frame` of assay names, sample identifiers, and colname samples
`metadata` | An optional argument of "ANY" class (usually list) for content describing the experiments
`drops` | A `list` of unmatched information (included after subsetting)

### Value

A `MultiAssayExperiment` object that can store experiment and phenotype data

### See Also

MultiAssayExperiment-class

### Examples

    ## Run the example ExperimentList
    example("ExperimentList")

    ## Create sample maps for each experiment
    exprmap <- data.frame(
        primary = c("Jack", "Jill", "Barbara", "Bob"),
        colname = c("array1", "array2", "array3", "array4"),
        stringsAsFactors = FALSE)

    methylmap <- data.frame(
        primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
        colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"),
        stringsAsFactors = FALSE)

    rnamap <- data.frame(
        primary = c("Jack", "Jill", "Bob", "Barbara"),
        colname = c("samparray1", "samparray2", "samparray3", "samparray4"),
        stringsAsFactors = FALSE)

    gistmap <- data.frame(
        primary = c("Jack", "Bob", "Jill"),
        colname = c("samp0", "samp1", "samp2"),
        stringsAsFactors = FALSE)

    ## Combine as a named list and convert to a DataFrame
    maplist <- list(Affy = exprmap, Methyl450k = methylmap,
        RNASeqGene = rnamap, GISTIC = gistmap)

    ## Create a sampleMap
    sampMap <- listToMap(maplist)
    ## Create an example phenotype data
    colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41,
        row.names = c("Jack", "Jill", "Bob", "Barbara"))

    ## Create a MultiAssayExperiment instance
    mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat,
        sampleMap = sampMap)

[Package MultiAssayExperiment version 1.16.0 Index]