limmaDE: Differential expression using limma

In markdunning/beadarray: Quality assessment and low-level analysis for Illumina BeadArray data

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)
}

markdunning/beadarray documentation built on May 9, 2019, 8:35 a.m.