runScanpyTSNE: runScanpyTSNE Computes tSNE from the given sce object and...

In compbiomed/singleCellTK: Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

runScanpyTSNE Computes tSNE from the given sce object and stores the tSNE computations back into the sce object

Description

runScanpyTSNE Computes tSNE from the given sce object and stores the tSNE computations back into the sce object

Usage

runScanpyTSNE(
  inSCE,
  useAssay = NULL,
  useReducedDim = "scanpyPCA",
  reducedDimName = "scanpyTSNE",
  dims = 40,
  perplexity = 30,
  externalReduction = NULL,
  seed = 12345
)

Arguments

inSCE	(sce) object on which to compute the tSNE
useAssay	Specify name of assay to use. Default is NULL, so useReducedDim param will be used instead.
useReducedDim	selected reduction method to use for computing tSNE. Default "scanpyPCA".
reducedDimName	Name of new reducedDims object containing Scanpy tSNE Default scanpyTSNE.
dims	Number of reduction components to use for tSNE computation. Default 40.
perplexity	Adjust the perplexity tuneable parameter for the underlying tSNE call. Default 30.
externalReduction	Pass DimReduc object if PCA computed through other libraries. Default NULL.
seed	Specify numeric value to set as a seed. Default 12345.

Value

Updated sce object with tSNE computations stored

Examples

data(scExample, package = "singleCellTK")
## Not run: 
sce <- runScanpyNormalizeData(sce, useAssay = "counts")
sce <- runScanpyFindHVG(sce, useAssay = "scanpyNormData", method = "seurat")
sce <- runScanpyScaleData(sce, useAssay = "scanpyNormData")
sce <- runScanpyPCA(sce, useAssay = "scanpyScaledData")
sce <- runScanpyFindClusters(sce, useReducedDim = "scanpyPCA")
sce <- runScanpyTSNE(sce, useReducedDim = "scanpyPCA")

## End(Not run)

compbiomed/singleCellTK documentation built on June 11, 2025, 9:45 a.m.