library(Seurat) library(sctree) markers <- sctree::FindAllMarkers( small_5050_mix, features = rownames(small_5050_mix@assays$RNA@data), test.use = "RangerDE") # Here we just extract the top 3 markers for each cluster top_markers <- do.call(rbind, lapply(split(markers, markers$cluster), head, 3)) top_markers <- top_markers$gene
Lets say we choose the top n markers from the former list and we did a flow
experiment ... HYPOTHETICALLY the marker distribution would resemble the rna
expression profile for which we have the function plot_flowstyle
top_markers
g <- plot_flowstyle(small_5050_mix, markernames = top_markers) g
We can also focus in one of the pannels (and check the color conventions)
g[1,2]
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