collect_classes-ConsensusPartitionList-method {cola} | R Documentation

## 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 <z.gu@dkfz.de>

### Examples

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

[Package cola version 1.8.1 Index]