doTSNE: Perform tSNE based dimension reduction

In minzheguo/SINCERA: An R implementation of SINCERA pipeline for processing single-cell RNA-seq data.

Description

Perform tSNE analysis on gene expression space or pca space

Usage

doTSNE(object, n = 2, use.fast = T, max.iter = 2000, seed = 0,
  feature.type = "pca", dims = 1:3, genes = NULL, use.scaled = F, ...)

Arguments

object	A sincera object
n	The number of tSNE dimensions to be extracted
use.fast	If TRUE, use Rtsne::Rtsne; otherwise, use tsne::tsne
max.iter	The maximum number of iteration
seed	The seed of randomness
feature.type	The input feature type for tSNE reduction, possible values include gene and pca
dims	If feature.type is pca, the pca components for tSNE
genes	If feature.type is genes, the set of genes for tSNE; if NULL, set to all genes
use.scaled	If TRUE, use the scaled expression for tSNE
use.scaled	If TRUE, use the scaled expression values of genes for tSNE; only take effect when the feature.type is gene

Details

When feature.type is "gene", genes with zero variance will be excluded prior to calling tSNE functions. When use.fast is TRUE, please refer to ?Rtsne::Rtsne for more parameters to control tSNE reduction. When use.fast is FALSE, please refer to ?tsne::tsne for more parameters to control tSNE reduction.

Value

The update sincera object with tsne results in the tsne slot

minzheguo/SINCERA documentation built on Feb. 3, 2021, 2:31 p.m.