MultiMeasure {consensus} | R Documentation

## MultiMeasure Constructor

### Description

Creates a `MultiMeasure` object from a set of 3 or more numeric matrices, in preparation to pass to `fitConsensus`.

### Usage

    MultiMeasure(names=NA_character_, data=list())

### Arguments

`names` | character vector contains the names of each data type (e.g. RNA-Seq, Agilent etc.). Must be the same `length` as `data`.
`data` | list of numeric matrices of identical `dim`, `rownames` and `colnames` where each matrix contains the measurements from the platform/condition described in `names`. Rows of each matrix correspond to genomic features and columns to samples. Must be the same length as, and have order correspond to, `names`.

### Details

A MultiMeasure contains a list of numeric matrices with identical dimensions and matching row names and column names, to which multiple row-linear models can be fit using `fitConsensus`. Users should pass a vector of `names` describing the platform/conditions the genomic measurements are made under, and a corresponding list of matrices to the `data` argument. A series of validity checks will be made on data correctness and a helpful error message will be returned if the structure does not conform to the above description.

### Value

a `MultiMeasure` object

### Author(s)

Tim Peters <t.peters@garvan.org.au>

### See Also

`MultiMeasure-class`

### Examples

    data(TCGA)
    tcga_mm <- MultiMeasure(names=c("U133A", "Huex", "Agilent", "RNA-Seq"),
    			data=list(U133A, Huex, Agilent, RNASeq))

[Package consensus version 1.4.0 Index]