getDecideTests: Differential expression analysis an multiplicity of the tests

In AgiMicroRna: Processing and Differential Expression Analysis of Agilent microRNA chips

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

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

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

## End(Not run)

AgiMicroRna documentation built on Nov. 8, 2020, 5:25 p.m.