dimension_reduction-DownSamplingConsensusPartition-method: Visualize column after dimension reduction

Description Usage Arguments Details Value Examples

Description

Visualize samples (the matrix columns) after dimension reduction

Usage

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## S4 method for signature 'DownSamplingConsensusPartition'
dimension_reduction(object, k, top_n = NULL,
    method = c("PCA", "MDS", "t-SNE", "UMAP"),
    control = list(),
    internal = FALSE, nr = 5000,
    p_cutoff = 0.05, remove = FALSE,
    scale_rows = TRUE, verbose = TRUE, ...)

Arguments

object

A DownSamplingConsensusPartition-class object.

k

Number of subgroups.

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.

nr

If number of matrix rows is larger than this value, random nr rows are used.

p_cutoff

Cutoff of p-value of class label prediction. Data points with values higher than it will be mapped with cross symbols.

remove

Whether to remove columns which have high p-values than the cutoff.

scale_rows

Whether to perform scaling on matrix rows.

verbose

Whether print messages.

...

Other arguments.

Details

This function is basically very similar as dimension_reduction,ConsensusPartition-method.

Value

No value is returned.

Examples

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cola documentation built on Nov. 8, 2020, 8:12 p.m.