RunMCDMAP: Run DiffusionMap on MCA cell and feature coordinates

In cbl-imagine/CellID: Unbiased Extraction of Single Cell Identity using Multiple Correspondence Analysis

Description

Run DiffusionMap on MCA cell and feature coordinates

Usage

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

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

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

Arguments

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

Value

Seurat or SingleCellExperiment object with MCDMAP stored in the reduction slot

Examples

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

cbl-imagine/CellID documentation built on July 22, 2020, 7:18 p.m.