R 中的Seurat::DotPlot绘制气泡图 2022-06

dotplot气泡图.png

#object是seurat对象，features是需要展示在横坐标轴上的genes

library(dplyr);library(ggtree);library(cowplot)
df <- DotPlot(object,features = features)$data

head(df).png

#获取气泡图中的相关信息，为构建层次聚类图作准备

mat <- df %>% dplyr::select(-pct.exp, -avg.exp.scaled) %>%  tidyr::pivot_wider
(names_from = features.plot, values_from = avg.exp ) %>% data.frame() 
row.names(mat) <- mat$id
mat <- mat[,-1]

head(mat).png

#计算不同细胞类型之间的相关性

clust <- hclust(dist(mat %>% as.matrix()))
ddgram <- as.dendrogram(clust) 

#绘制层次聚类图

ggtree_plot <- ggtree::ggtree(ddgram,branch.length="none")+
        geom_tippoint(color="#FDAC4F", shape=8, size=3)

#绘制气泡图总图

df$id <-  factor(df$id , levels = clust$labels[clust$order])
dotplot <- ggplot(df,aes(x=features.plot,y = id,size = pct.exp, color = avg.exp.scaled))+
        geom_point() + 
        scale_size("% detected", range = c(0,6)) +
        scale_y_discrete(position = "right") +
        scale_color_gradientn(colours = viridis::viridis(20),
                              guide = guide_colorbar(ticks.colour = "black",frame.colour = "black"),
                              name = "Average\nexpression") +
        cowplot::theme_cowplot() + 
        ylab("") + xlab("Markers") + theme_bw() +
        theme(
            axis.text.x = element_text(size=10, angle=0, hjust=0.5, color="black"),
            axis.text.y = element_text(size=12, color="black"),
            axis.title = element_text(size=14)
        )
ggtree_plot_yset <- ggtree_plot + aplot::ylim2(dotplot)
    p <- plot_grid(ggtree_plot_yset,NULL,dotplot, nrow = 1, 
                   rel_widths = c(0.5,-0.025, 2), 
                   align = 'h')

#保存图片

pdf("dotplot.pdf",height=8,width=8)
print(p)
dev.off()

完整代码>>>github.com