单细胞出图稍微改改

更改横轴顺序（根据实际需要）

sce.all$group <- factor(x =sce.all$group, levels = c("PB","ecrs","necrs"))
p <- DotPlot(sce.all, 
             features = unique(top3$gene),
             group.by = "group",
             assay='RNA'  )  + coord_flip()

自带图美化一下

DimPlot(sce.all,
                 reduction = "umap", #聚类方式
                 label = F,
                 raster=FALSE,
                 group.by = "celltype", #按照组别设置
                 #cols= paletteer_d("ggsci::category20_d3"),  # 颜色可以在这里设置,也可以在后面设置
                 pt.size = 0.8,#设置点的大小  
                 repel = T)+#标注有点挤，repel=T可以让排列更加合理  
  #NoLegend()+  
  scale_color_manual(values = alpha(paletteer::paletteer_d('ggsci::category20c_d3'), 0.65)) +  #此处设置颜色可以调节深浅
  labs(x = "UMAP1", y = "UMAP2")+    
  theme(axis.text.y = element_blank(),   
        axis.ticks.y = element_blank(),   
        axis.text.x = element_blank(),   
        axis.ticks.x = element_blank()) +
  theme(panel.border = element_rect(fill=NA,color="black", size=1, linetype="solid"))


DoHeatmap(sce.all,
          features = top10$gene,
          group.by = "cluster",
          size=3)+
          scale_fill_gradientn(colors = c("navy","white","firebrick3"))

DotPlot(sce.all, 
             features = unique(top3$gene),
             group.by = "cluster",
             assay='RNA'  ) +
  coord_flip()+theme_bw()+#去除背景，旋转图片  
  theme(panel.grid = element_blank(),  
        axis.text.x=element_text(angle=90,hjust = 1,vjust=0.5))+#文字90度呈现  
  scale_color_gradientn(values = seq(0,1,0.2),colors = c('#330066','#336699','#66CC66','#FFCC33'))+#颜色渐变设置  
  labs(x=NULL,y=NULL)+guides(size=guide_legend(order=3)) 


VlnPlot(sce.all, 
                         features = genes_to_check,
                         stack = T,#T 在同一张图上显示
                         flip = T,#倒置
                         pt.size = 0)  #点的大小