plotReducedDimMC: Scater plotReducedDim for MCA like dimensionality Reduction

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

Description

Small modification of the Scater plotReducedDim function to enable plotting features for mca like dimensionality reduction.

Usage

plotReducedDimMC(X, reduction = "MCA", dims = c(1, 2),
  features = NULL, size.feature = 3, size.feature.text = 5,
  as.text = FALSE, ...)

Arguments

X	a Single Cell Experiment Object
reduction	Which dimensionality reduction to use. If not specified, searches for mca.
dims	Dimensions to plot, must be a two-length numeric vector specifying x- and y-dimensions
features	character vector of features to plot, must be present in the specified dimension loadings
size.feature	integer indicating size of geom_point for features
size.feature.text	integer indicating size of geom_text for features
as.text	logical indicating as to include text label for feature plotting, will produce warning if TRUE and length(features) > 50.
...	Other arguments passed to plotReducedDim

Value

A ggplot object

Examples

scePBMC <- as.SingleCellExperiment(seuratPbmc)
scePBMC <- RunMCA(scePBMC, nmcs = 5)
plotReducedDimMC(scePBMC)

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