Description Usage Arguments Value Examples
Function for computing the basline support for multivariate features given gamma and beta parameters.
1 2 | computeMultivariateSupport(seMat, FeatureSets, gamma = 0.1,
beta = 0.95, distance = "euclidean", verbose = TRUE)
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seMat |
SummariziedExperiment with an assay in [0, 1], with each column corresponding to a sample and each row corresponding to a feature; usually in quantile form. |
FeatureSets |
The multivariate features in list or matrix form. In list form, each list element should be a vector of individual features; in matrix form, it should be a binary matrix with rownames being individual features and column names being the names of the feature sets. |
gamma |
Parameter for selecting radius around each support point (0 < gamma < 1). By default gamma = 0.1. |
beta |
Parameter for eliminating outliers (0 < beta <= 1). By default beta=0.95. |
distance |
Type of distance to be calculated between points. Any type of distance that can be passed on to the dist function can be used (default 'euclidean'). |
verbose |
Logical indicating whether to print status related messages during computation (defaults to TRUE). |
A list with elements: Support: a matrix indicating which samples were included in the support. Baseline_list: a list where each element is the baseline of a multivariate feature. featureMat: the multivariate features in matrix form. alpha: the expected number of divergent multivariate features per sample. gamma: the gamma parameter used for baseline computation. distance: the type of distance used for baselien computation.
1 2 3 4 | 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)
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