RunMCA: Run Multiple Correspondence Analysis

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

Description

Run Multiple Correspondence Analysis

Usage

RunMCA(X, nmcs, features, reduction.name, slot, ...)

## S3 method for class 'matrix'
RunMCA(X, nmcs = 50, features = NULL,
  reduction.name = "MCA", ...)

## S3 method for class 'Seurat'
RunMCA(X, nmcs = 50, features = NULL,
  reduction.name = "mca", slot = "data", assay = DefaultAssay(X),
  ...)

## S3 method for class 'SingleCellExperiment'
RunMCA(X, nmcs = 50, features = NULL,
  reduction.name = "MCA", slot = "logcounts", ...)

Arguments

X	Seurat, SingleCellExperiment or matrix object
nmcs	number of components to compute and store, default set to 30
features	character vector of feature names. If not specified all features will be taken.
reduction.name	name of the reduction default set to "MCA" for SingleCellExperiment and mca
slot	Which slot to pull expression data from?
...	other aruments passed to methods
assay	Name of Assay MCA is being run on

Value

Seurat or SCE object with MCA calculation stored in the reductions slot.

Examples

seuratPbmc <- RunMCA(seuratPbmc, nmcs = 5)

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