normalizeMethyLumiSet {methylumi} | R Documentation

## Normalize a MethyLumiSet, accounting for dye bias

### Description

The Illumina GoldenGate methylation platform uses two colors, one to represent the unmethylated state and the other to represent the methylated state. This function corrects that dye bias and recalculates the betas based on the corrected intensities.

For HumanMethylation27 data, the function does nothing.

For HumanMethylation450 data, the function delegates to normalizeViaControls() the task of scaling red and green intensities against a reference array (chip) which uses the closest-to-equal chip (i.e., which.min(abs(R.G.ratio - 1))).

The code to do this is based on code from the 'minfi' package and uses the built-in red and green normalization control probes on the hm450 arrays to scale the channels of the samples, so that a consistent degree of dye bias is maintained for Infinium II probes across an experiment or set of experiments.

### Usage

    normalizeMethyLumiSet(x, beta.cuts = c(0.2, 0.8), mapfun = c("atan", "ratio"))

### Arguments

`x` | A MethyLumiSet object
`beta.cuts` | Two numeric values with the first less than the second and between 0 and 1, representing the beta cutoffs that will be used when determining the median intensities to which to correct. See details below.
`mapfun` | Either "atan" or "ratio". See details below.

### Details

For HumanMethylation450 data, the function delegates to normalizeViaControls() the task of scaling red and green intensities against a reference array (chip) which defaults to the first chip in a set. The code to do this is based on code from the 'minfi' package and uses the built-in normalization controls to scale the channels of the samples, so that a consistent degree of dye bias is maintained for Infinium II probes across an experiment or set of experiments. The remainder of the documentation below is specific to GoldenGate data.

The Illumina GoldenGate methylation platform uses two colors, one to represent the unmethylated state and the other to represent the methylated state. This function corrects that dye bias and recalculates the betas based on the corrected intensities.

As a first step, the medians for each of Cy3 and Cy5 are calculated at high and low betas, representing the (nearly) fully methylated state and the (nearly) fully unmethylated states. Values of Cy3 and Cy5 that are negative are set to zero for this process. Then, the Cy5 medians are adjusted to match those of the Cy3 channel, thereby correcting the dye bias.

To map the new intensities back to betas, one of two map functions can be used. The default is the atan(Cy3/Cy5). The ratio maps using the function (Cy3/Cy3+Cy5). The differences should be very small, but we feel that the atan map function is probably the mathematically appropriate way of doing this.

### Value

A new "MethyLumiSet" that contains the corrected betas and the adjusted intensities.

### Author(s)

Sean Davis <sdavis2@mail.nih.gov>

### Examples

    ## Read in sample information
    samps <- read.table(system.file("extdata/samples.txt",
                                    package = "methylumi"),sep="\t",header=TRUE)
    ## Perform the actual data reading
    ## This is an example of reading data from an
    ## Sentrix Array format file (actually two files,
    ## one for data and one for QC probes)
    mldat <- methylumiR(system.file('extdata/exampledata.samples.txt',package='methylumi'),
                        qcfile=system.file('extdata/exampledata.controls.txt',package="methylumi"),
                        sampleDescriptions=samps)
    mldatnorm <- normalizeMethyLumiSet(mldat)

[Package methylumi version 2.30.0 Index]