computeMultivariateBinaryMatrix: Compute the binary matrix with digitized divergence coding
In wikum/divergence.preSE: Divergence Computations

Description Usage Arguments Value Examples

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

1	computeMultivariateBinaryMatrix(Mat, Baseline)

`Mat`	Matrix of data 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()

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

baseMat = breastTCGA_Mat[, breastTCGA_Group == "NORMAL"]
baseMat.q = computeQuantileMatrix(baseMat)
baseline = computeMultivariateSupport(Mat=baseMat.q, FeatureSets=msigdb_Hallmarks)
dataMat = breastTCGA_Mat[, breastTCGA_Group != "NORMAL"]
dataMat.q = computeQuantileMatrix(dataMat)
divMat = computeMultivariateBinaryMatrix(Mat=dataMat.q, Baseline=baseline)