varianceBeadStabilise {blima} | R Documentation

## Bead level VST.

### Description

This function does variance stabilising step on bead level.

### Usage

    varianceBeadStabilise(b, normalizationMod = NULL, quality = "qua",
        channelInclude = "bgf", channelOutput = "vst")

### Arguments

`b` | List of beadLevelData objects (or single object).
`normalizationMod` | NULL for normalization of all input b. Otherwise specifies logical vector of the length equal to the number of arrays in b or list of such vectors if b is a list of beadLevelData classes.
`quality` | Quality to analyze, default is "qua".
`channelInclude` | This field allows user to set channel with weights which have to be in 0,1. All zero weighted items are excluded from t-test. You can turn this off by setting this NULL. This option may be used together with bacgroundCorrect method or/and with beadarray QC (defaults to "bgf").
`channelOutput` | Output from VST.

### Author(s)

Vojtěch Kulvait

### Examples

    if(require("blimaTestingData") && interactive())
    {
        #To perform background correction, variance stabilization and quantile normalization.
        data(blimatesting)
        #Prepare logical vectors corresponding to conditions A(groups1Mod), E(groups2Mod) and both(c).
        groups1 = "A";
        groups2 = "E";
        sampleNames = list()
        processingMod = list()
        for(i in 1:length(blimatesting))
        {
            p = pData(blimatesting[[i]]@experimentData$phenoData)
            processingMod[[i]] = p$Group %in% c(groups1, groups2);
            sampleNames[[i]] = p$Name
        }
        #Background correction and quantile normalization followed by testing including log2TransformPositive transformation.
        blimatesting = bacgroundCorrect(blimatesting, normalizationMod = processingMod, channelBackgroundFilter="bgf")
        blimatesting = nonPositiveCorrect(blimatesting, normalizationMod = processingMod, channelCorrect="GrnF",  channelBackgroundFilter="bgf", channelAndVector="bgf")
        blimatesting = varianceBeadStabilise(blimatesting, normalizationMod = processingMod,
                quality="GrnF", channelInclude="bgf", channelOutput="vst")
        blimatesting = quantileNormalize(blimatesting, normalizationMod = processingMod,
                channelNormalize="vst", channelOutput="qua", channelInclude="bgf")
    }else
    {
        print("To run this example, please install blimaTestingData package from bioconductor by running BiocManager::install('blimaTestingData').");
    }

[Package blima version 1.24.0 Index]