computeMultivariateBinaryMatrix {divergence} | R Documentation |
Function for obtaining the binary form for a matrix for multivariate divergence of data given a baseline range
computeMultivariateBinaryMatrix(seMat, Baseline)
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() |
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"] 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)