Performs normalization and/or log2 transformation

Description

This function performs normalization and/or log2 transformation on gene expression data.

Usage

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    preprocess(exprsObj,log2=TRUE, norm="ALL", destname=NULL)

Arguments

exprsObj

An eSet object where its assay data will be normalized

log2

Performs logarithmic transformation of base 2 prior to any normalzation. The default value is TRUE

norm

The user may define a specific normalization method rather than "ALL" which is the default case. The available abbreviations are described in the details section

destname

Here we define the destination path and the name of the jpeg file with the density plots. The default path is the working directory

Details

The available normalization methods are:
Mean-centering normalization "mc"
z-score normalization "z"
Quantile normalization "q"
Cyclic loess normalization "cl"
Mean-centering normalization and log2 transformation "mcL2"
z-score normalization and log2 transformation "zL2"
Quantile normalization and log2 transformation "qL2"
Cyclic loess normalization and log2 transformation "clL2"

Value

rawdata

The initial gene expression values

mc.normdata

The values after 'mean-centering' normalization

z.normdata

The values after 'z-score' normalization

q.normdata

The values after 'quantile' normalization

cl.normdata

The values after 'cyclic loess' normalization

mcL2.normdata

The values after 'mean-centering' normalization and log2

zL2.normdata

The values after 'z-score' normalization and log2

qL2.normdata

The values after 'quantile' normalization and log2

clL2.normdata

The values after 'cyclic loess' normalization and log2

Author(s)

Argiris Sakellariou

Examples

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library(mAPKLData)
data(mAPKLData)
varLabels(mAPKLData)
breast <- sampling(Data=mAPKLData, valPercent=40, classLabels="type", seed=135)
normTrainData <- preprocess(exprsObj=breast$trainData)