limmaDE {beadarray} | R Documentation

## Differential expression using limma

### Description

Function to perform a standard limma analysis using a single command.

### Usage

    limmaDE(summaryData, SampleGroup, DesignMatrix = NULL, makeWts = TRUE, ...)

### Arguments

`summaryData` | ExpressionSetIllumina object
`SampleGroup` | Name of column in phenoData that will be used to construct sample groups for analysis
`DesignMatrix` | Optional design matrix
`makeWts` | if TRUE weights will be calculated for each array
`...` | Other arguments that lmFit can accept

### Details

The function automates the steps used in a typical limma analysis. Firstly, the lmFit is used to fit a linear model from the specified column in `phenoData`. Array weights can be calculated (arrayWeights) and used in the fit. A contrast matrix of all possible contrasts is created (makeContrasts) and fitted (makeContrasts). The empirical Bayes shrinkage of variances is then applied (eBayes). The design matrix, contrast matrix and array weights can all be extracted for the resulting object.

### Value

a limmaResults object

### Author(s)

Mark Dunning

### Examples

    if(require(beadarrayExampleData)){
      data(exampleSummaryData)
      rawdata <- channel(exampleSummaryData, "G")
      normdata <- normaliseIllumina(rawdata)
      limmaResults <- limmaDE(normdata, SampleGroup = "SampleFac")
      limmaResults
      DesignMatrix(limmaResults)
    }

[Package beadarray version 2.30.0 Index]