GeneHeatmap: Heatmap visualization of the gene markers identified by...

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

Heatmap visualization of the gene markers identified by FindAllGeneMarkers

Description

The GeneHeatmap function enables drawing a heatmap of the gene markers identified by FindAllGeneMarkers, where the cell are grouped by the clustering.

Usage

GeneHeatmap.SingleCellExperiment(object, clustering.type, gene.markers)

## S4 method for signature 'SingleCellExperiment'
GeneHeatmap(object, clustering.type = "manual", gene.markers = NULL)

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 using the "CalcSilhInfo" function. Default is "manual".
gene.markers	a data frame of the gene markers generated by FindAllGeneMarkers function. To accelerate the drawing, filtering the dataframe by selecting e.g. top 10 genes is recommended.

Value

nothing

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,r=1,k=5) # Use L=200
sce <- RunPCA(sce,p=5)
sce <- HierarchicalClustering(sce)
sce <- SelectKClusters(sce,K=5)
gene_markers <- FindAllGeneMarkers(sce,log2fc.threshold = 0.5,min.pct = 0.5)
top10_log2FC <- SelectTopGenes(gene_markers,top.N=10,
criterion.type="log2FC",inverse=FALSE)
GeneHeatmap(sce,clustering.type = "manual",
 gene.markers = top10_log2FC)

elolab/ILoReg documentation built on March 28, 2022, 1:17 a.m.