pickDimReduction: Pick the dimensionality reduction method for a dataset that...

In netSmooth: Network smoothing for scRNAseq

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)

netSmooth documentation built on Nov. 8, 2020, 5:33 p.m.