In jspaezp/sctree: Tree based analysis of single rna-seq clusters

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

Visualizing the expected outcome of a flow cytometry experiment

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]

jspaezp/sctree documentation built on April 30, 2020, 10:36 p.m.