VlnPlot: Gene expression visualization using violin plots

In ILoReg: ILoReg: a tool for high-resolution cell population identification from scRNA-Seq data

Description

The VlnPlot function enables visualizing expression levels of a gene, or multiple genes, across clusters using Violin plots.

Usage

VlnPlot.SingleCellExperiment(
  object,
  clustering.type,
  genes,
  return.plot,
  rotate.x.axis.labels
)

## S4 method for signature 'SingleCellExperiment'
VlnPlot(
  object,
  clustering.type = "manual",
  genes = NULL,
  return.plot = FALSE,
  rotate.x.axis.labels = FALSE
)

Arguments

object	of SingleCellExperiment class
clustering.type	"manual" or "optimal". "manual" refers to the clustering formed using the "SelectKClusters" function and "optimal" to the clustering formed using the "CalcSilhInfo" function. Default is "manual".
genes	a character vector denoting the gene names that are visualized
return.plot	return.plot whether to return the ggplot2 object
rotate.x.axis.labels	a logical denoting whether the x-axis labels should be rotated 90 degrees. or just draw it. Default is FALSE.

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 <- HierarchicalClustering(sce)
sce <- SelectKClusters(sce,K=5)
VlnPlot(sce,genes=c("CD3D","CD79A","CST3"))

ILoReg documentation built on Nov. 8, 2020, 8:20 p.m.