preprocess {mAPKL} | R Documentation

## Performs normalization and/or log2 transformation

### Description

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

### Usage

        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

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

[Package mAPKL version 1.16.0 Index]