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Python的Scanpy包和Seurat包一样,是单细胞数据处理的利器,其中,Scanpy中有一种堆积的小提琴图,可以很好的展示marker的表达情况,但是在Seurat中并没有内置命令。因此,我自己尝试提取数据并用ggplot2包来画该图。

首先来展示以下画图的成果,如图

首先来展示以下画图的成果,如图

那么直接上命令吧!

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###载入需要的R包
library(Seurat)
library(dplyr)
library(tidyr)
library(ggplot2)
##load测试数据
data<-readRDS("cluster_1.afterclu.rds")
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##第一个函数从Seurat对象中获取表达值并转化为需要的格式tidy
gotData<-function(seurat.obj,features,groups){
mat<-GetAssayData(data,assay = "RNA",slot = "data")[features,]
plotData<-mat%>%
as.data.frame()%>%
tibble::rownames_to_column(var="gene")%>%
as_tibble()%>%
tidyr::pivot_longer(names_to = "cell",values_to="exp",cols=2:(ncol(mat)+1))
cellmeta<-data@meta.data%>%
tibble::rownames_to_column(var="cell")%>%
as_tibble()%>%
select(cell,sym(groups))
plotData<-plotData%>%
left_join(cellmeta,by="cell")%>%
setNames(c("gene","cell","value","cellID"))
plotData
}
##第二个函数画图
plot_stacked_violin<-function(plotData,xlab,ylab,cols){
ggplot(plotData,aes(y=cellID,x=value,fill=cellID))+
geom_violin()+
facet_wrap(.~gene)+
theme_test()+
xlab(xlab)+
ylab(ylab)+
scale_fill_manual(values = cols)+
theme(panel.spacing=unit(0,"cm"),
strip.background = element_rect(fill="transparent",color = "white"),
axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
panel.border = element_rect(size=0.7,colour = "black"),
strip.text = element_text(size=10,face = "italic"),
axis.text.y = element_text(size = 11.5,face="bold"),
axis.title.y = element_text(size = 13))+
NoLegend()
}

下面是使用方法

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plot_stacked_violin(gotData(data,c("CD7","KLRB1","NKG7"),"integrated_snn_res.0.1"),"","Cell cluster",c("#8dd3c7","#ffffb3","#bebada","#fb8072"))

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