VlnPlot: Gene expression visualization using violin plots

Description Usage Arguments Value Examples

Description

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

Usage

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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

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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.