adjColorBias.quantile: Color bias adjustment of Illumina Infinium methylaton...

In lumi: BeadArray Specific Methods for Illumina Methylation and Expression Microarrays

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)

lumi documentation built on Nov. 8, 2020, 5:27 p.m.