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New data visualization methods in v2.0

We’ll demonstrate visualization techniques in Seurat using our previously computed Seurat object from the 2,700 PBMC tutorial. You can download that here

library(Seurat)
load(file = "~/Downloads/seurat_resources/pbmc3k_final.Rda")
pbmc
## An object of class seurat in project 10X_PBMC 
##  13714 genes across 2638 samples.

Five visualizations of marker gene expression

features.plot <- c("LYZ", "CCL5", "IL32", "PTPRCAP", "FCGR3A", "PF4")
# Joy plots - from ggjoy. Visualize single cell expression distributions in
# each cluster
JoyPlot(object = pbmc, features.plot = features.plot, nCol = 2)