Function to do differential expression analysis, using ANOVA models

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Description

This function takes an object of class maiges and do differential expression analysis for the genes onto dataset, comparing more than two samples using ANalysis Of VAriance (ANOVA) models.

Usage

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deGenesANOVA(data=NULL, eBayes=FALSE, retOrig=FALSE,
             retF=FALSE, doClust=TRUE, ...)

Arguments

data

object of class maigesANOVA.

eBayes

logical indicating the use or not (default) of empirical Bayes statistics implemented in limma package.

retOrig

logical indicating if the object of class MArrayLM from limma package must be returned. Defaults to FALSE.

retF

logical asking to return the results associated with the F test (TRUE) or with the individual contrasts (FALSE - default).

doClust

logical indicating if the object generated from this analysis will be used for cluster analysis. Defaults to TRUE.

...

additional parameters to function lmFit.

Details

The object of class maigesANOVA of the argument data is created by the function designANOVA. This function calculate statistics and p-values using the function lmFit from package limma.

Value

The result of this function is an object of class MArrayLM when retOrig is TRUE. When it is FALSE, the result is an object of class maigesDE if doClust if FALSE or of class maigesDEcluster if it is TRUE.

Author(s)

Gustavo H. Esteves <gesteves@vision.ime.usp.br>

See Also

designANOVA, lmFit, MArrayLM.

Examples

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## Loading the dataset
data(gastro)

## Constructing a maigesANOVA object for the 'Tissue' sample label using
## default model (simple linear model with intercept) and contrasts (all
## parameters are equal between themselves)
gastro.ANOVA = designANOVA(gastro.summ, factors="Tissue")

## Fitting the ANOVA model designed by the above command
gastro.ANOVAfit = deGenesANOVA(gastro.ANOVA, retF=TRUE)
gastro.ANOVAfit

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