最近有小伙伴问道一个问题，如何在一个单细胞UMAP/TSNE图上展示多个marker基因的表达，乍一看挺简单的，后来也是思考了一些时间，慢慢解决了这个问题。
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首先，Seurat中的FeaturePlot函数能够完成两种marker的组合，但是不能超过两个，否则报错！
#使用Featureplot标记基因
FeaturePlot(human_data, features = c("CD3E", "IL1B"),
cols = c("lightgrey", "blue", "blue"),
blend=T,blend.threshold=0)
#三个基因的时候就不行了
FeaturePlot(human_data, features = c("CD3E", "IL1B","CD74"),
cols = c("lightgrey", "blue", "blue"),
blend=T,blend.threshold=0)
# Error in FeaturePlot(human_data, features = c("CD3E", "IL1B", "CD74"), :
# Blending feature plots only works with two features
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后来我想到用ggplot叠加geom_point,但是有问题，不能显示渐变。
#找到表达这些基因的细胞坐标，添加上去
p1=DimPlot(human_data,group.by = 'celltype',
cols = c("grey","grey",
"grey","grey","grey"),
pt.size = 1)+NoLegend()
gene1 <- "CD3E"
gene2 <- "CD74"
gene3 <- "IL1B"
pos_gene=human_data@[email protected]
pos_gene1=pos_gene[human_data@assays$RNA@data[gene1,]>0,]
pos_gene2=pos_gene[human_data@assays$RNA@data[gene2,]>0,]
pos_gene3=pos_gene[human_data@assays$RNA@data[gene3,]>0,]
p1+geom_point(data = as.data.frame(pos_gene1),
aes(x=UMAP_1,y=UMAP_2),
shape = 16,size = 0.5, color="blue")+
geom_point(data = as.data.frame(pos_gene2),
aes(x=UMAP_1,y=UMAP_2),
shape = 16,size = 0.5, color="blue")+
geom_point(data = as.data.frame(pos_gene3),
aes(x=UMAP_1,y=UMAP_2),
shape = 16,size = 0.5, color="blue")
image
所以最后我直接想着用ggplot实现，首先区分三个颜色看一下效果，看是不是有覆盖！可见三种基因都标记上了，而且表达量是渐变的。****
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