collect_classes-ConsensusPartitionList-method: Collect classes from ConsensusPartitionList object

In jokergoo/cola: A Framework for Consensus Partitioning

Collect classes from ConsensusPartitionList object

Description

Collect classes from ConsensusPartitionList object

Usage

## S4 method for signature 'ConsensusPartitionList'
collect_classes(object, k, show_column_names = FALSE,
    column_names_gp = gpar(fontsize = 8),
    anno = get_anno(object), anno_col = get_anno_col(object),
    simplify = FALSE, ...)

Arguments

object	A ConsensusPartitionList-class object returned by run_all_consensus_partition_methods.
k	Number of subgroups.
show_column_names	Whether to show column names in the heatmap (which is the column name in the original matrix).
column_names_gp	Graphics parameters for column names.
anno	A data frame of annotations for the original matrix columns. By default it uses the annotations specified in run_all_consensus_partition_methods.
anno_col	A list of colors (color is defined as a named vector) for the annotations. If anno is a data frame, anno_col should be a named list where names correspond to the column names in anno.
simplify	Internally used.
...	Pass to draw,HeatmapList-method.

Details

There are following panels in the plot:

• a heatmap showing partitions predicted from all methods where the top annotation is the consensus partition summarized from partitions from all methods, weighted by mean silhouette scores in every single method.

• a row barplot annotation showing the mean silhouette scores for different methods.

The row clustering is applied on the dissimilarity matrix calculated by cl_dissimilarity with the comembership method.

The brightness of the color corresponds to the silhouette scores for the consensus partition in each method.

Value

No value is returned.

Author(s)

Zuguang Gu <[e-mail]>

Examples

data(golub_cola)
collect_classes(golub_cola, k = 3)

jokergoo/cola documentation built on Feb. 29, 2024, 1:41 a.m.