adjColorBias.quantile {lumi} | R Documentation

## Color bias adjustment of Illumina Infinium methylaton microarrays using smooth quantile normalization

### Description

Color bias adjustment of Illumina Infinium methylaton microarrays using smooth quantile normalization `smoothQuantileNormalization`

### Usage

    adjColorBias.quantile(methyLumiM, refChannel = c("green", "red"), logMode = TRUE, verbose = TRUE,...)

### Arguments

`methyLumiM` | a MethyLumiM object or any eSet object with "methylated" and "unmethylated" data matrix element in the assayData slot
`refChannel` | the reference color channel for color bias adjustment
`logMode` | whether perform the adjustment in log scale or not
`verbose` | whether print extra information during processing
`...` | other parameters used by `smoothQuantileNormalization`

### Details

Perform color bias adjustment of Illumina Infinium methylaton microarrays. It requires the input methyLumiM object includes the color channel information in the featureData. Basically, there should be a "COLOR_CHANNEL" column in the data.frame returned by pData(featureData(methyLumiM)).

The basic idea of color bias adjustment is to treat it as the normalization between two color channels. It uses smooth quantile normalization `smoothQuantileNormalization` to normalize two color channels.

### Value

Return an object (same class as input methyLumiM) with updated "methylated" and "unmethylated" data matrix after color bias adjustment.

### Author(s)

Pan DU

### See Also

See Also `lumiMethyC`, `smoothQuantileNormalization` and `adjColorBias.ssn`

### Examples

    data(example.lumiMethy)
    # before adjustment
    plotColorBias1D(example.lumiMethy)
    lumiMethy.adj = adjColorBias.quantile(example.lumiMethy)
    # after adjustment
    plotColorBias1D(lumiMethy.adj)

[Package lumi version 2.36.0 Index]