Description Usage Arguments Value Examples
The GeneHeatmap function enables drawing a heatmap of the gene markers identified by FindAllGeneMarkers, where the cell are grouped by the clustering.
1 2 3 4 | 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
1 2 3 4 5 6 7 8 9 10 11 12 13 | 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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