pickDimReduction,matrix-method {netSmooth}R Documentation

Pick the dimensionality reduction method for a dataset that gives the 2D embedding with the highest entropy

Description

Pick the dimensionality reduction method for a dataset that gives the 2D embedding with the highest entropy

Usage

## S4 method for signature 'matrix'
pickDimReduction(x, flavors = c("pca", "tsne", "umap"), is.counts = TRUE)

## S4 method for signature 'SummarizedExperiment'
pickDimReduction(x)

## S4 method for signature 'Matrix'
pickDimReduction(x, flavors = c("pca", "tsne", "umap"), is.counts = TRUE)

## S4 method for signature 'DelayedMatrix'
pickDimReduction(x, flavors = c("pca", "tsne", "umap"), is.counts = TRUE)

Arguments

x

matrix or SummarizedExperiment object [GENES x SAMPLES]

flavors

list of dimensionality reduction algorithms to try. Currently the options are "pca", "tsne" and "umap"

is.counts

logical: is exprs count data

Value

name of dimensionality reduction method that gives the highest 2d entropy

Examples

x <- matrix(rnbinom(60000, size=1, prob = .1), ncol=100)
pickDimReduction(x)
[Package netSmooth version 1.7.0 Index]