🤩 scRNA-seq | 吐血整理的单细胞入门教程（基础可视化）（五）

rm(list = ls())
library(tidyverse)
library(scater)
library(SingleCellExperiment)
library(ggsci)
library(scater)

counts <- read.table("./molecules.txt", sep = "\t")
annotation <- read.table("./annotation.txt", sep = "\t", header = TRUE)

# 注意assays必须是matrix
tung <- SingleCellExperiment(
  assays = list(counts = as.matrix(counts)),
  colData = annotation
)
assay(tung, "logcounts") <- log2(counts(tung) + 1)
colData(tung)$total_counts <- colSums(counts(tung))
tung

cell_info <- as.data.frame(colData(tung))
head(cell_info)

cell_info %>% 
  ggplot(aes(x = batch, y = total_counts)) +
  geom_violin(aes(fill= batch)) + 
  theme_bw() + 
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1))+
  scale_fill_npg()

tung %>% 
  ggcells(aes(x = batch, y = total_counts)) + 
  geom_violin(aes(fill = batch)) + 
  theme_bw() + 
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1))+
  scale_fill_lancet()

tung %>% 
  ggcells(aes(x = batch, y = ENSG00000198938), exprs_values = "logcounts") + 
  geom_violin(aes(fill = batch)) +
  theme_bw() + 
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1))+
  scale_fill_aaas()