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  "Title": "Consensus Clustering",
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  "Description": "Clustering, or cluster analysis, is a widely used\ntechnique in bioinformatics to identify groups of similar\nbiological data points. Consensus clustering is an extension to\nclustering algorithms that aims to construct a robust result\nfrom those clustering features that are invariant under\ndifferent sources of variation. For the reference, please cite\nthe following paper: Yousefi, Melograna, et. al., (2023)\n<doi:10.3389/fmicb.2023.1170391>.",
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    "adj_mat",
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    "cluster_relabel",
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    "consensus_matrix_data_prtrb",
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    "multiview_cluster_gen",
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    "multiview_pam_gen",
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    {
      "page": "adj_conv",
      "title": "Convert adjacency function to the affinity matrix",
      "topics": [
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      ]
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      "title": "Covert data matrix to adjacency matrix",
      "topics": [
        "adj_mat"
      ]
    },
    {
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      "title": "Count the number of clusters based on stability score.",
      "topics": [
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      ]
    },
    {
      "page": "cluster_relabel",
      "title": "Relabeling clusters based on cluster similarities",
      "topics": [
        "cluster_relabel"
      ]
    },
    {
      "page": "coCluster_matrix",
      "title": "Calculate the Co-cluster matrix for a given set of clustering results.",
      "topics": [
        "coCluster_matrix"
      ]
    },
    {
      "page": "connectivity_matrix",
      "title": "Build connectivity matrix",
      "topics": [
        "connectivity_matrix"
      ]
    },
    {
      "page": "consensus_matrix",
      "title": "Calculate consensus matrix for data perturbation consensus clustering",
      "topics": [
        "consensus_matrix"
      ]
    },
    {
      "page": "consensus_matrix_data_prtrb",
      "title": "Calculate consensus matrix for data perturbation consensus clustering",
      "topics": [
        "consensus_matrix_data_prtrb"
      ]
    },
    {
      "page": "consensus_matrix_multiview",
      "title": "Calculate consensus matrix for multi-data consensus clustering",
      "topics": [
        "consensus_matrix_multiview"
      ]
    },
    {
      "page": "gaussian_clusters",
      "title": "Generate clusters of data points from Gaussian distribution with randomly generated parameters",
      "topics": [
        "gaussian_clusters"
      ]
    },
    {
      "page": "gaussian_clusters_with_param",
      "title": "Generate clusters of data points from Gaussian distribution with given parameters",
      "topics": [
        "gaussian_clusters_with_param"
      ]
    },
    {
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      "title": "Generate clusters of data points from Gaussian-mixture-model distributions with randomly generated parameters",
      "topics": [
        "gaussian_mixture_clusters"
      ]
    },
    {
      "page": "generate_data_prtrb",
      "title": "Generation mechanism for data perturbation consensus clustering",
      "topics": [
        "generate_data_prtrb"
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    },
    {
      "page": "generate_gaussian_data",
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    },
    {
      "page": "generate_method_prtrb",
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      "topics": [
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      ]
    },
    {
      "page": "generate_multiview",
      "title": "Multiview generation",
      "topics": [
        "generate_multiview"
      ]
    },
    {
      "page": "hir_clust_from_adj_mat",
      "title": "Hierarchical clustering from adjacency matrix",
      "topics": [
        "hir_clust_from_adj_mat"
      ]
    },
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      "title": "Build indicator matrix",
      "topics": [
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      ]
    },
    {
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      "title": "Similarity between different clusters",
      "topics": [
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      ]
    },
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      "title": "Logit function",
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      ]
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