GeneHeatmap | R Documentation |
The GeneHeatmap function enables drawing a heatmap of the gene markers identified by FindAllGeneMarkers, where the cell are grouped by the clustering.
GeneHeatmap.SingleCellExperiment(object, clustering.type, gene.markers) ## S4 method for signature 'SingleCellExperiment' GeneHeatmap(object, clustering.type = "manual", gene.markers = NULL)
object |
of |
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. |
nothing
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)
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