top_rows_heatmap-matrix-method: Heatmap of top rows from different top-value methods

In jokergoo/cola: A Framework for Consensus Partitioning

Heatmap of top rows from different top-value methods

Description

Heatmap of top rows from different top-value methods

Usage

## S4 method for signature 'matrix'
top_rows_heatmap(object, all_top_value_list = NULL,
    top_value_method = all_top_value_methods(),
    bottom_annotation = NULL,
    top_n = round(0.25*nrow(object)), scale_rows = TRUE, ...)

Arguments

object	A numeric matrix.
all_top_value_list	Top-values that have already been calculated from the matrix. If it is NULL the values are calculated by methods in top_value_method argument.
top_value_method	Methods defined in all_top_value_methods.
bottom_annotation	A HeatmapAnnotation-class object.
top_n	Number of top rows to show in the heatmap.
scale_rows	Whether to scale rows.
...	Pass to Heatmap.

Details

The function makes heatmaps where the rows are scaled (or not scaled) for the top n rows from different top-value methods.

The top n rows are used for subgroup classification in cola analysis, so the heatmaps show which top-value method gives better candidate rows for the classification.

Value

No value is returned.

Author(s)

Zuguang Gu <[e-mail]>

Examples

set.seed(123)
mat = matrix(rnorm(1000), nrow = 100)
top_rows_heatmap(mat, top_n = 25)

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