dimension_reduction-ConsensusPartition-method: Visualize column after dimension reduction

In jokergoo/cola: A Framework for Consensus Partitioning

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(), color_by = NULL,
    internal = FALSE, nr = 5000,
    silhouette_cutoff = 0.5, remove = FALSE,
    scale_rows = object@scale_rows, verbose = TRUE, ...)

Arguments

object	A ConsensusPartition-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.
color_by	If annotation table is set, an annotation name can be set here.
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.
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 to perform scaling on matrix rows.
verbose	Whether print messages.
...	Pass to dimension_reduction,matrix-method.

Value

Locations of the points.

Author(s)

Zuguang Gu <[e-mail]>

Examples

data(golub_cola)
dimension_reduction(golub_cola["ATC", "skmeans"], k = 3)

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