consensus_heatmap-ConsensusPartition-method: Heatmap for the consensus matrix

Description Usage Arguments Details Value Author(s) Examples

Description

Heatmap for the consensus matrix

Usage

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## S4 method for signature 'ConsensusPartition'
consensus_heatmap(object, k, internal = FALSE,
    anno = get_anno(object), anno_col = get_anno_col(object),
    show_row_names = !internal, ...)

Arguments

object

a ConsensusPartition-class object.

k

number of partitions.

internal

used internally.

anno

a data frame with column annotations of samples. By default it used the annotations specified in consensus_partition or run_all_consensus_partition_methods.

anno_col

a list of colors (a named vector) for the annotations.

show_row_names

whether plot row names on the consensus heatmap (which are the column names in the original matrix)

...

other arguments

Details

For row i and column j in the consensus matrix, the value of corresponding x_ij is the probability of sample i and sample j being in a same subgroup from the repetitive partitionings.

There are following heatmaps from left to right:

Value

No value is returned.

Author(s)

Zuguang Gu <[email protected]>

Examples

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data(cola_rl)
consensus_heatmap(cola_rl["sd", "hclust"], k = 3)

jokergoo/cola documentation built on Nov. 13, 2018, 1:22 p.m.