AnnotationScatterPlot: Visualiation of a custom annotation over nonlinear...

AnnotationScatterPlotR Documentation

Visualiation of a custom annotation over nonlinear dimensionality reduction

Description

The AnnotationScatterPlot enables visualizing arbitrary class labels over the nonliner dimensionality reduction, e.g. t-SNE or UMAP.

Usage

AnnotationScatterPlot.SingleCellExperiment(
  object,
  annotation,
  return.plot,
  dim.reduction.type,
  point.size,
  show.legend
)

## S4 method for signature 'SingleCellExperiment'
AnnotationScatterPlot(
  object,
  annotation = NULL,
  return.plot = FALSE,
  dim.reduction.type = "",
  point.size = 0.7,
  show.legend = FALSE
)

Arguments

object

of SingleCellExperiment class

annotation

a character vector, factor or numeric for the class labels.

return.plot

return.plot whether to return the ggplot2 object or just draw it. Default is FALSE.

dim.reduction.type

"tsne" or "umap". Default is tsne.

point.size

point size. Default is 0.7.

show.legend

a logical denoting whether to show the legend on the right side of the plot. Default is TRUE.

Value

ggplot2 object if return.plot=TRUE

Examples

library(SingleCellExperiment)
sce <- SingleCellExperiment(assays = list(logcounts = pbmc3k_500))
sce <- PrepareILoReg(sce)
## These settings are just to accelerate the example, use the defaults.
sce <- RunParallelICP(sce,L=2,threads=1,C=0.1,k=5,r=1)
sce <- RunPCA(sce,p=5)
sce <- RunTSNE(sce)
sce <- HierarchicalClustering(sce)
sce <- SelectKClusters(sce,K=5)
## Change the names to the first five alphabets and Visualize the annotation.
custom_annotation <- plyr::mapvalues(metadata(sce)$iloreg$clustering.manual,
                                     c(1,2,3,4,5),
                                     LETTERS[1:5])
AnnotationScatterPlot(sce,
                      annotation = custom_annotation,
                      return.plot = FALSE,
                      dim.reduction.type = "tsne",
                      show.legend = FALSE)



elolab/iloreg documentation built on March 27, 2022, 4:19 a.m.