RunMCTSNE: Run TSNE on MCA fetures and cells coordinates

In Cortalak/cellID: Unbiased Extraction of Single Cell Identity using Multiple Correspondence Analysis

Description

Run TSNE on MCA fetures and cells coordinates

Usage

RunMCTSNE(X, reduction, dims, features, reduction.name, ...)

## S3 method for class 'Seurat'
RunMCTSNE(X, reduction = "mca", dims = seq(50),
  features = NULL, reduction.name = "mctsne",
  assay = DefaultAssay(X), ...)

## S3 method for class 'SingleCellExperiment'
RunMCTSNE(X, reduction = "MCA",
  dims = seq(50), features = NULL, reduction.name = "MCTSNE", ...)

Arguments

X	Seurat or SingleCellExperiment object
reduction	Which dimensionality reduction to use, must be based on MCA.
dims	A vector of integers indicating which dimensions to use with reduction embeddings and loadings for distance calculation.
features	Character vector of feature names to subset feature coordinates. If not specified will take all features available from specified reduction Loadings.
reduction.name	name of the created dimensionlaity reduction, default set to "mca" for Seurat and "MCA" for SCE.
...	other arguments passed to methods or Rtsne::Rtsne
assay	Seurat assay slot. When not specified set with DefaultAssay(X)

Value

Seurat or SingleCellExperiment object with MCTSNE stored in the reduction slot

Examples

seuratPbmc <- RunMCA(seuratPbmc, nmcs = 5)
seuratPbmc <- RunMCTSNE(seuratPbmc, dims = seq(5))

Cortalak/cellID documentation built on Aug. 3, 2020, 9:01 p.m.