Differential expression analysis an multiplicity of the tests

Description

It Uses the decideTests function of the 'limma' package to classify the list of genes as up, down or not significant after correcting by the multiplicity of the tests.

Usage

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getDecideTests(fit2, DEmethod, MTestmethod, PVcut,verbose=FALSE)

Arguments

fit2

MArrayLM object

DEmethod

method for decideTests, only 'separate' or 'nestedF' are implemented. see decideTests in limma package.

MTestmethod

method for multiple test, choices are 'none','BH', 'BY', ... see p.adjust

PVcut

p value threshold to declare significant features

verbose

logical, if TRUE prints out output

Value

A 'TestResults' object of the 'limma' package It prints out the number of UP and DOWN genes for every contrasts according to the p value limit specified

Author(s)

Pedro Lopez-Romero

References

Smyth, G. K. (2005). Limma: linear models for microarray data. In: 'Bioinformatics and Computational Biology Solutions using R and Bioconductor'. R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, W. Huber (eds), Springer, New York, pages 397–420.

See Also

An overview of miRNA differential expression analysis is given in basicLimma

Examples

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## Not run: 
DE=getDecideTests(fit2,
        DEmethod="separate",
        MTestmethod="BH",
        PVcut=0.10,
	verbose=TRUE)

## End(Not run)