computeMultivariateBinaryMatrix {divergence} | R Documentation

## Compute the binary matrix with digitized divergence coding

### Description

Function for obtaining the binary form for a matrix for multivariate divergence of data given a baseline range

### Usage

    computeMultivariateBinaryMatrix(seMat, Baseline)

### Arguments

`seMat` | SummarizedExperiment with assay to be digitized, in [0, 1], with each column corresponding to a sample and each row corresponding to a feature; usually in quantile form.
`Baseline` | A Baseline object; this corresponds to the output of findMultivariateGammaWithSupport() or computeMultivariateSupport()

### Value

A matrix with the same columns as Mat, with rows being the multivariate features, containing the binary form data.

### Examples

    baseMat = breastTCGA_Mat[, breastTCGA_Group == "NORMAL"]
    seMat.base = SummarizedExperiment(assays=list(data=baseMat))
    assays(seMat.base)$quantile = computeQuantileMatrix(seMat.base)
    baseline = computeMultivariateSupport(seMat=seMat.base, FeatureSets=msigdb_Hallmarks)
    dataMat = breastTCGA_Mat[, breastTCGA_Group != "NORMAL"]
    seMat = SummarizedExperiment(assays=list(data=dataMat))
    assays(seMat)$quantile = computeQuantileMatrix(seMat)
    Mat.div = computeMultivariateBinaryMatrix(seMat=seMat, Baseline=baseline)

[Package divergence version 1.6.0 Index]