Description Usage Arguments Value
Consensus matrix is calculated using the Cluster-based Similarity Partitioning Algorithm (CSPA). For each clustering solution a binary similarity matrix is constructed from the corresponding cell labels: if two cells belong to the same cluster, their similarity is 1, otherwise the similarity is 0. A consensus matrix is calculated by averaging all similarity matrices.
1 | consensus_matrix(clusts, k)
|
clusts |
a matrix containing clustering solutions in columns |
k |
umber of clusters |
consensus matrix
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