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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

pbmc <- readRDS(file = "~/Downloads/seurat_resources/pbmc3k_final.rds")
## 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")
# Ridge plots - from ggridges. Visualize single cell expression
# distributions in each cluster
RidgePlot(object = pbmc, features.plot = features.plot, nCol = 2)