绘制单细胞分析组织中细胞数量和细胞比例柱状图

今天绘制一下单细胞分析结果组织中细胞数量和细胞比例柱状图，代码如下：

1. 安装需要的R包

install.packages(“Seurat”)

install.packages(“patchwork”)

install.packages(“reshape2”)

install.packages(“RcolorBrewer”)

install.packages(“scales”)

install.packages(“ggplot2”)

install.packages(“tidyverse”)

1. 导入所需要的R包

library(Seurat)

library(patchwork)

library(reshape2)

library(RcolorBrewer)

library(ggplot2)

library(tidyverse)

library(scales)

1. 代码展示

数据下载

wget https://cf.10xgenomics.com/samples/cell/pbmc3k/pbmc3k_filtered_gene_bc_matrices.tar.gz

tar -zxvf pbmc3k_filtered_gene_bc_matrices.tar.gz

#分析所需要的文件三个在filtered_gene_bc_matrices/hg19/

pbmc.data <- Read10X(data.dir = “filtered_gene_bc_matrices/hg19/”)

# Initialize the Seurat object with the raw (non-normalized data).

pbmc <- CreateSeuratObject(counts = pbmc.data, project = “pbmc3k”, min.cells = 3, min.features = 200)

# Normalizing the data

pbmc <- NormalizeData(pbmc, normalization.method = “LogNormalize”, scale.factor = 10000)

#Identification of highly variable features

pbmc <- FindVariableFeatures(pbmc, selection.method = “vst”, nfeatures = 2000)

all.genes <- rownames(pbmc)

pbmc <- ScaleData(pbmc, features = all.genes)

#Run non-linear dimensional reduction (UMAP/tSNE)

pbmc <- RunUMAP(pbmc, dims = 1:10)

#开始绘图

colourCount = length(unique(pbmc@meta.data$celltype))

getPalette = colorRampPalette(brewer.pal(9, “Set1”))

celltype_colors <- getPalette(colourCount)

#提取样本和细胞数据，并且进行长宽数据转换

plotC <- table(pbmc@meta.data$sample, pbmc@meta.data$celltype) %>% melt()

colnames(plotC) <- c(“Sample”, “CellType”,”Number”)

#绘制每个组织中细胞数目柱状图

pC1 <- ggplot(data = data_plotC, aes(x = Sample, y = Number, fill = CellType)) +

geom_bar(stat = “identity”, width=0.8,aes(group=CellType),position=”stack”)+

scale_fill_manual(values=celltype_colors) +

theme_bw()+

theme(panel.grid =element_blank()) +

labs(x=””,y=”Average number”)+

theme(axis.text = element_text(size=12, colour = “black”))+

theme(axis.title.y = element_text(size=12, colour = “black”))+

theme(panel.border = element_rect(size = 1, linetype = “solid”, colour = “black”))+

theme(axis.text.x = element_text(angle = 45,hjust = 0.8, vjust = 0.6))

#绘制每个组织中细胞比例柱状图

pC2 <- ggplot(data = plotC, aes(x = Sample, y = Number, fill = CellType)) +

geom_bar(stat = “identity”, width=0.8,aes(group=CellType),position=”fill”)+

scale_fill_manual(values=celltype_colors) +

theme_bw()+

theme(panel.grid =element_blank()) +

labs(x=””,y=”Cell proportion”)+

scale_y_continuous(labels = percent)+ ####用来将y轴移动位置

theme(axis.text = element_text(size=12, colour = “black”))+

theme(axis.title.y = element_text(size=12, colour = “black”))+

theme(panel.border = element_rect(size = 1, linetype = “solid”, colour = “black”))+

theme(axis.text.x = element_text(angle = 45,hjust = 0.8, vjust = 0.6))#让横轴上的标签倾斜45度

#两个图片进行拼图

pC <- pC1 + pC2 + plot_layout(ncol = 2, widths = c(1,1),guides = ‘collect’)

#保存图片

ggsave(pC,file=”plotC.pdf”,width = 7, height = 5)