{ "_id": "6a1adc191d7bb097a09e9463", "Package": "cola", "Type": "Package", "Title": "A Framework for Consensus Partitioning", "Version": "2.19.0", "Date": "2026-01-30", "Authors@R": "person(\"Zuguang\", \"Gu\", email = \"guzuguang@suat-sz.edu.cn\", role = c(\"aut\", \"cre\"),\ncomment = c('ORCID'=\"0000-0002-7395-8709\"))", "Description": "Subgroup classification is a basic task in genomic data\nanalysis, especially for gene expression and DNA methylation\ndata analysis. It can also be used to test the agreement to\nknown clinical annotations, or to test whether there exist\nsignificant batch effects. The cola package provides a general\nframework for subgroup classification by consensus\npartitioning. It has the following features: 1. It modularizes\nthe consensus partitioning processes that various methods can\nbe easily integrated. 2. It provides rich visualizations for\ninterpreting the results. 3. It allows running multiple methods\nat the same time and provides functionalities to\nstraightforward compare results. 4. It provides a new method to\nextract features which are more efficient to separate\nsubgroups. 5. It automatically generates detailed reports for\nthe complete analysis. 6. It allows applying consensus\npartitioning in a hierarchical manner.", "URL": "https://github.com/jokergoo/cola,\nhttps://jokergoo.github.io/cola_collection/", "VignetteBuilder": "knitr", "biocViews": "Clustering, GeneExpression, Classification, Software", "License": "MIT + file LICENSE", "Config/pak/sysreqs": "libpng-dev libxml2-dev libssl-dev perl", "Repository": "https://bioc.r-universe.dev", "Date/Publication": "2026-04-28 12:49:26 UTC", "RemoteUrl": "https://github.com/bioc/cola", "RemoteRef": "HEAD", "RemoteSha": "713af79d9c6a6714d3283b0d50d81328e15cc448", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-30 09:02:20 UTC", "User": "root" }, "Author": "Zuguang Gu [aut, cre] (ORCID: )", "Maintainer": "Zuguang Gu ", "MD5sum": "34a231f25ae31e487203a4c692fb9ae2", "_user": "bioc", "_type": "src", "_file": "cola_2.19.0.tar.gz", "_fileid": "6fca5551e21450ca09d143ff23d6729b92ecb477b65cfc6a1a49fb5baec8ca09", "_filesize": 4266285, "_sha256": 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"get_anno_col" ] }, { "page": "get_anno_col-HierarchicalPartition-method", "title": "Get annotation colors", "topics": [ "get_anno_col,HierarchicalPartition-method" ] }, { "page": "get_anno-ConsensusPartition-method", "title": "Get annotations", "topics": [ "get_anno,ConsensusPartition-method" ] }, { "page": "get_anno-ConsensusPartitionList-method", "title": "Get annotations", "topics": [ "get_anno,ConsensusPartitionList-method" ] }, { "page": "get_anno-dispatch", "title": "Method dispatch page for get_anno", "topics": [ "get_anno" ] }, { "page": "get_anno-DownSamplingConsensusPartition-method", "title": "Get annotations", "topics": [ "get_anno,DownSamplingConsensusPartition-method" ] }, { "page": "get_anno-HierarchicalPartition-method", "title": "Get annotations", "topics": [ "get_anno,HierarchicalPartition-method" ] }, { "page": "get_children_nodes-HierarchicalPartition-method", "title": "Test whether a node is a leaf node", "topics": [ "get_children_nodes", "get_children_nodes,HierarchicalPartition-method" ] }, { "page": "get_classes-ConsensusPartition-method", "title": "Get subgroup labels", "topics": [ "get_classes,ConsensusPartition-method" ] }, { "page": "get_classes-ConsensusPartitionList-method", "title": "Get subgroup labels", "topics": [ "get_classes,ConsensusPartitionList-method" ] }, { "page": "get_classes-dispatch", "title": "Method dispatch page for get_classes", "topics": [ "get_classes" ] }, { "page": "get_classes-DownSamplingConsensusPartition-method", "title": "Get subgroup labels", "topics": [ "get_classes,DownSamplingConsensusPartition-method" ] }, { "page": "get_classes-HierarchicalPartition-method", "title": "Get class IDs from the HierarchicalPartition object", "topics": [ "get_classes,HierarchicalPartition-method" ] }, { "page": "get_consensus-ConsensusPartition-method", "title": "Get consensus matrix", "topics": [ "get_consensus", "get_consensus,ConsensusPartition-method" ] }, { "page": "get_matrix-ConsensusPartition-method", "title": "Get the original matrix", "topics": [ "get_matrix,ConsensusPartition-method" ] }, { "page": "get_matrix-ConsensusPartitionList-method", "title": "Get the original matrix", "topics": [ "get_matrix,ConsensusPartitionList-method" ] }, { "page": "get_matrix-dispatch", "title": "Method dispatch page for get_matrix", "topics": [ "get_matrix" ] }, { "page": "get_matrix-DownSamplingConsensusPartition-method", "title": "Get the original matrix", "topics": [ "get_matrix,DownSamplingConsensusPartition-method" ] }, { "page": "get_matrix-HierarchicalPartition-method", "title": "Get the original matrix", "topics": [ "get_matrix,HierarchicalPartition-method" ] }, { "page": "get_membership-ConsensusPartition-method", "title": "Get membership matrix", "topics": [ "get_membership,ConsensusPartition-method" ] }, { "page": "get_membership-ConsensusPartitionList-method", "title": "Get membership matrix", "topics": [ "get_membership,ConsensusPartitionList-method" ] }, { "page": "get_membership-dispatch", "title": "Method dispatch page for get_membership", "topics": [ "get_membership" ] }, { "page": "get_param-ConsensusPartition-method", "title": "Get parameters", "topics": [ "get_param", "get_param,ConsensusPartition-method" ] }, { "page": "get_signatures-ConsensusPartition-method", "title": "Get signature rows", "topics": [ "get_signatures,ConsensusPartition-method" ] }, { "page": "get_signatures-dispatch", "title": "Method dispatch page for get_signatures", "topics": [ "get_signatures" ] }, { "page": "get_signatures-DownSamplingConsensusPartition-method", "title": "Get signature rows", "topics": [ "get_signatures,DownSamplingConsensusPartition-method" ] }, { "page": "get_signatures-HierarchicalPartition-method", "title": "Get signatures rows", "topics": [ "get_signatures,HierarchicalPartition-method" ] }, { "page": "get_stats-ConsensusPartition-method", "title": "Get statistics", "topics": [ "get_stats,ConsensusPartition-method" ] }, { "page": "get_stats-ConsensusPartitionList-method", "title": "Get statistics", "topics": [ "get_stats,ConsensusPartitionList-method" ] }, { "page": "get_stats-dispatch", "title": "Method dispatch page for get_stats", "topics": [ "get_stats" ] }, { "page": "golub_cola", "title": "Example ConsensusPartitionList object from Golub dataset", "topics": [ "golub_cola" ] }, { "page": "golub_cola_ds", "title": "Example DownSamplingConsensusPartition object from Golub dataset", "topics": [ "golub_cola_ds" ] }, { "page": "golub_cola_rh", "title": "Example HierarchicalPartition object from Golub dataset", "topics": [ "golub_cola_rh" ] }, { "page": "hierarchical_partition", "title": "Hierarchical partition", "topics": [ "hierarchical_partition" ] }, { "page": "HierarchicalPartition-class", "title": "The HierarchicalPartition class", "topics": [ "HierarchicalPartition", "HierarchicalPartition-class" ] }, { "page": "is_best_k-ConsensusPartition-method", "title": "Test whether the current k is the best/optional k", "topics": [ "is_best_k,ConsensusPartition-method" ] }, { "page": "is_best_k-ConsensusPartitionList-method", "title": "Test whether the current k is the best/optional k", "topics": [ "is_best_k,ConsensusPartitionList-method" ] }, { "page": "is_best_k-dispatch", "title": "Method dispatch page for is_best_k", "topics": [ "is_best_k" ] }, { "page": "is_leaf_node-HierarchicalPartition-method", "title": "Test whether a node is a leaf node", "topics": [ "is_leaf_node", "is_leaf_node,HierarchicalPartition-method" ] }, { "page": "is_stable_k-ConsensusPartition-method", "title": "Test whether the current k corresponds to a stable partition", "topics": [ "is_stable_k,ConsensusPartition-method" ] }, { "page": "is_stable_k-ConsensusPartitionList-method", "title": "Test whether the current k corresponds to a stable partition", "topics": [ "is_stable_k,ConsensusPartitionList-method" ] }, { "page": "is_stable_k-dispatch", "title": "Method dispatch page for is_stable_k", "topics": [ "is_stable_k" ] }, { "page": "knee_finder2", "title": "Find the knee/elbow of a list of sorted points", "topics": [ "knee_finder2" ] }, { "page": "knitr_add_tab_item", "title": "Add JavaScript tab in the report", "topics": [ "knitr_add_tab_item" ] }, { "page": "knitr_insert_tabs", "title": "Generate the HTML fragment for the JavaScript tabs", "topics": [ "knitr_insert_tabs" ] }, { "page": "map_to_entrez_id", "title": "Map to Entrez IDs", "topics": [ "map_to_entrez_id" ] }, { "page": "max_depth-HierarchicalPartition-method", "title": "Max depth of the hierarchy", "topics": [ "max_depth", "max_depth,HierarchicalPartition-method" ] }, { "page": "membership_heatmap-ConsensusPartition-method", "title": "Heatmap of membership in each partition", "topics": [ "membership_heatmap", "membership_heatmap,ConsensusPartition-method" ] }, { "page": "merge_node_param", "title": "Parameters to merge branches in subgroup dendrogram.", "topics": [ "merge_node_param" ] }, { "page": "merge_node-HierarchicalPartition-method", "title": "Merge node", "topics": [ "merge_node", "merge_node,HierarchicalPartition-method" ] }, { "page": "ncol-ConsensusPartition-method", "title": "Number of columns in the matrix", "topics": [ "ncol,ConsensusPartition-method" ] }, { "page": "ncol-ConsensusPartitionList-method", "title": "Number of columns in the matrix", "topics": [ "ncol,ConsensusPartitionList-method" ] }, { "page": "ncol-dispatch", "title": "Method dispatch page for ncol", "topics": [ "ncol" ] }, { "page": "ncol-DownSamplingConsensusPartition-method", "title": "Number of columns in the matrix", "topics": [ "ncol,DownSamplingConsensusPartition-method" ] }, { "page": "ncol-HierarchicalPartition-method", "title": "Number of columns in the matrix", "topics": [ "ncol,HierarchicalPartition-method" ] }, { "page": "node_info-HierarchicalPartition-method", "title": "Information on the nodes", "topics": [ "node_info", "node_info,HierarchicalPartition-method" ] }, { "page": "node_level-HierarchicalPartition-method", "title": "Information on the nodes", "topics": [ "node_level", "node_level,HierarchicalPartition-method" ] }, { "page": "nrow-ConsensusPartition-method", "title": "Number of rows in the matrix", "topics": [ "nrow,ConsensusPartition-method" ] }, { "page": "nrow-ConsensusPartitionList-method", "title": "Number of rows in the matrix", "topics": [ "nrow,ConsensusPartitionList-method" ] }, { "page": "nrow-dispatch", "title": "Method dispatch page for nrow", "topics": [ "nrow" ] }, { "page": "nrow-HierarchicalPartition-method", "title": "Number of rows in the matrix", "topics": [ "nrow,HierarchicalPartition-method" ] }, { "page": "PAC", "title": "The proportion of ambiguous clustering (PAC score)", "topics": [ "PAC" ] }, { "page": "plot_ecdf-ConsensusPartition-method", "title": "Plot the empirical cumulative distribution (eCDF) curve of the consensus matrix", "topics": [ "plot_ecdf", "plot_ecdf,ConsensusPartition-method" ] }, { "page": "predict_classes-ConsensusPartition-method", "title": "Predict classes for new samples based on cola classification", "topics": [ "predict_classes,ConsensusPartition-method" ] }, { "page": "predict_classes-dispatch", "title": "Method dispatch page for predict_classes", "topics": [ "predict_classes" ] }, { "page": "predict_classes-matrix-method", "title": "Predict classes for new samples based on signature centroid matrix", "topics": [ "predict_classes,matrix-method" ] }, { "page": "print.hc_table_suggest_best_k", "title": "Print the hc_table_suggest_best_k object", "topics": [ "print.hc_table_suggest_best_k" ] }, { "page": "recalc_stats", "title": "Recalculate statistics in the ConsensusPartitionList object", "topics": [ "recalc_stats" ] }, { "page": "register_NMF", "title": "Register NMF partitioning method", "topics": [ "register_NMF" ] }, { "page": "register_partition_methods", "title": "Register user-defined partitioning methods", "topics": [ "register_partition_methods" ] }, { "page": "register_SOM", "title": "Register SOM partitioning method", "topics": [ "register_SOM" ] }, { "page": "register_top_value_methods", "title": "Register user-defined top-value methods", "topics": [ "register_top_value_methods" ] }, { "page": "relabel_class", "title": "Relabel class labels according to the reference labels", "topics": [ "relabel_class" ] }, { "page": "remove_partition_methods", "title": "Remove partitioning methods", "topics": [ "remove_partition_methods" ] }, { "page": "remove_top_value_methods", "title": "Remove top-value methods", "topics": [ "remove_top_value_methods" ] }, { "page": "rownames-ConsensusPartition-method", "title": "Row names of the matrix", "topics": [ "rownames,ConsensusPartition-method" ] }, { "page": "rownames-ConsensusPartitionList-method", "title": "Row names of the matrix", "topics": [ "rownames,ConsensusPartitionList-method" ] }, { "page": "rownames-dispatch", "title": "Method dispatch page for rownames", "topics": [ "rownames" ] }, { "page": "rownames-HierarchicalPartition-method", "title": "Row names of the matrix", "topics": [ "rownames,HierarchicalPartition-method" ] }, { "page": "run_all_consensus_partition_methods", "title": "Consensus partitioning for all combinations of methods", "topics": [ "run_all_consensus_partition_methods" ] }, { "page": "select_partition_number-ConsensusPartition-method", "title": "Several plots for determining the optimized number of subgroups", "topics": [ "select_partition_number", "select_partition_number,ConsensusPartition-method" ] }, { "page": "show-ConsensusPartition-method", "title": "Print the ConsensusPartition object", "topics": [ "show,ConsensusPartition-method" ] }, { "page": "show-ConsensusPartitionList-method", "title": "Print the ConsensusPartitionList object", "topics": [ "show,ConsensusPartitionList-method" ] }, { "page": "show-dispatch", "title": "Method dispatch page for show", "topics": [ "show" ] }, { "page": "show-DownSamplingConsensusPartition-method", "title": "Print the DownSamplingConsensusPartition object", "topics": [ "show,DownSamplingConsensusPartition-method" ] }, { "page": "show-HierarchicalPartition-method", "title": "Print the HierarchicalPartition object", "topics": [ "show,HierarchicalPartition-method" ] }, { "page": "split_node-HierarchicalPartition-method", "title": "Split node", "topics": [ "split_node", "split_node,HierarchicalPartition-method" ] }, { "page": "suggest_best_k-ConsensusPartition-method", "title": "Suggest the best number of subgroups", "topics": [ "suggest_best_k,ConsensusPartition-method" ] }, { "page": "suggest_best_k-ConsensusPartitionList-method", "title": "Suggest the best number of subgroups", "topics": [ "suggest_best_k,ConsensusPartitionList-method" ] }, { "page": "suggest_best_k-dispatch", "title": "Method dispatch page for suggest_best_k", "topics": [ "suggest_best_k" ] }, { "page": "suggest_best_k-HierarchicalPartition-method", "title": "Guess the best number of partitions", "topics": [ "suggest_best_k,HierarchicalPartition-method" ] }, { "page": "test_between_factors", "title": "Test whether a list of factors are correlated", "topics": [ "test_between_factors" ] }, { "page": "test_to_known_factors-ConsensusPartition-method", "title": "Test correspondance between predicted subgroups and known factors", "topics": [ "test_to_known_factors,ConsensusPartition-method" ] }, { "page": "test_to_known_factors-ConsensusPartitionList-method", "title": "Test correspondance between predicted classes and known factors", "topics": [ "test_to_known_factors,ConsensusPartitionList-method" ] }, { "page": "test_to_known_factors-dispatch", "title": "Method dispatch page for test_to_known_factors", "topics": [ "test_to_known_factors" ] }, { "page": "test_to_known_factors-DownSamplingConsensusPartition-method", "title": "Test correspondance between predicted subgroups and known factors", "topics": [ "test_to_known_factors,DownSamplingConsensusPartition-method" ] }, { "page": "test_to_known_factors-HierarchicalPartition-method", "title": "Test correspondance between predicted classes and known factors", "topics": [ "test_to_known_factors,HierarchicalPartition-method" ] }, { "page": "top_elements_overlap", "title": "Overlap of top elements from different metrics", "topics": [ "top_elements_overlap" ] }, { "page": "top_rows_heatmap-ConsensusPartition-method", "title": "Heatmap of top rows", "topics": [ "top_rows_heatmap,ConsensusPartition-method" ] }, { "page": "top_rows_heatmap-ConsensusPartitionList-method", "title": "Heatmap of top rows from different top-value methods", "topics": [ "top_rows_heatmap,ConsensusPartitionList-method" ] }, { "page": "top_rows_heatmap-dispatch", "title": "Method dispatch page for top_rows_heatmap", "topics": [ "top_rows_heatmap" ] }, { "page": "top_rows_heatmap-HierarchicalPartition-method", "title": "Heatmap of top rows from different top-value 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