Extract.HierarchicalPartition.RdSubset the HierarchicalPartition object
# S3 method for HierarchicalPartition
[(x, i)A HierarchicalPartition-class object.
Index. The value should be numeric or a node ID.
On each node, there is a ConsensusPartition-class object.
Note you cannot get a sub-hierarchy of the partition.
A ConsensusPartition-class object.
data(golub_cola_rh)
golub_cola_rh["01"]
#> A 'ConsensusPartition' object with k = 2, 3, 4.
#> On a matrix with 3910 rows and 35 columns.
#> Top rows (391) are extracted by 'ATC' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 150 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes"
#> [3] "collect_plots" "collect_stats"
#> [5] "colnames" "compare_partitions"
#> [7] "compare_signatures" "consensus_heatmap"
#> [9] "dimension_reduction" "functional_enrichment"
#> [11] "get_anno" "get_anno_col"
#> [13] "get_classes" "get_consensus"
#> [15] "get_matrix" "get_membership"
#> [17] "get_param" "get_signatures"
#> [19] "get_stats" "is_best_k"
#> [21] "is_stable_k" "membership_heatmap"
#> [23] "ncol" "nrow"
#> [25] "plot_ecdf" "predict_classes"
#> [27] "rownames" "select_partition_number"
#> [29] "show" "suggest_best_k"
#> [31] "test_to_known_factors" "top_rows_heatmap"