Consensus Clustering for Different Sample Coverage Data

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Documentation for package ‘ccml’ version 1.1.0

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callNCW Calculate normalized consensus weight(NCW) matrix based on permutation.
ccml A two-step consensus clustering inputing multiple predictive labels with different sample coverages (missing labels)
example_data The input data for example
plotCompareCW Plot of original consensus weights vs. normalized consensus weights grouping by the number of co-appeared percent of clustering(non-missing).
randConsensusMatrix Calculate consensus weight matrix based on the permuted input label matrix. Internal function used by 'callNCW'
spectralClusteringAffinity Perform spectral clustering algorithms for an affinity matrix, using SNFtool::spectralClustering.