dimension_reduction-ConsensusPartition-method {cola}R Documentation

Visualize column after dimension reduction

Description

Visualize samples (the matrix columns) after dimension reduction

Usage

## S4 method for signature 'ConsensusPartition'
dimension_reduction(object, k, top_n = NULL,
    method = c("PCA", "MDS", "t-SNE", "UMAP"),
    control = list(),
    internal = FALSE,
    silhouette_cutoff = 0.5, remove = FALSE,
    scale_rows = TRUE, verbose = TRUE, ...)

Arguments

object

A ConsensusPartition-class object.

k

Number of partitions.

top_n

Top n rows to use. By default it uses all rows in the original matrix.

method

Which method to reduce the dimension of the data. MDS uses cmdscale, PCA uses prcomp. t-SNE uses Rtsne. UMAP uses umap.

control

A list of parameters for Rtsne or umap.

internal

Internally used.

silhouette_cutoff

Cutoff of silhouette score. Data points with values less than it will be mapped with cross symbols.

remove

Whether to remove columns which have less silhouette scores than the cutoff.

scale_rows

Whether perform scaling on matrix rows.

verbose

Whether print messages.

...

Other arguments.

Value

No value is returned.

Author(s)

Zuguang Gu <z.gu@dkfz.de>

Examples

data(cola_rl)
dimension_reduction(cola_rl["sd", "kmeans"], k = 3)

[Package cola version 1.0.1 Index]