RunTSNE: Barnes-Hut implementation of t-Distributed Stochastic...

In elolab/ILoReg: ILoReg: a tool for high-resolution cell population identification from scRNA-Seq data

Barnes-Hut implementation of t-Distributed Stochastic Neighbor Embedding (t-SNE)

Description

Run nonlinear dimensionality reduction using t-SNE with the PCA-transformed consensus matrix as input.

Usage

RunTSNE.SingleCellExperiment(object, perplexity)

## S4 method for signature 'SingleCellExperiment'
RunTSNE(object, perplexity = 30)

Arguments

object	of SingleCellExperiment class
perplexity	perplexity of t-SNE

Value

object of SingleCellExperiment class

Examples

library(SingleCellExperiment)
sce <- SingleCellExperiment(assays = list(logcounts = pbmc3k_500))
sce <- PrepareILoReg(sce)
## These settings are just to accelerate the example, use the defaults.
sce <- RunParallelICP(sce,L=2,threads=1,C=0.1,k=5,r=1)
sce <- RunPCA(sce,p=5)
sce <- RunTSNE(sce)

elolab/ILoReg documentation built on March 28, 2022, 1:17 a.m.