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") # Ridge plots - from ggridges. Visualize single cell expression # distributions in each cluster RidgePlot(object = pbmc, features.plot = features.plot, nCol = 2)