ggplot作图实现线条注释-气泡图展示单细胞cluster与c

好看的图千千万，我就中意这一款。关于作图的注释，有很多种方法，有段时间，我很中意线条式的注释。一般情况，用AI直接画挺方便，但是还是想使用代码进行实现。发现ggh4x包有类似的效果，可以实现，所以这里演示一下。我们的演示示例式关于单细胞marker基因气泡图的注释，至于其他的图，基于ggplot作图的都可以使用这样的方式进行注释。

当然了，在尝试过程中，我们尝试拓展了效果，例如增粗线条，修改注释颜色，文字颜色等等，我们的效果如下：

image.png

获取作图数据：

setwd("/home/ks_ts/data_analysis/ggh4x/")

library(Seurat)
library(ggh4x)
library(ggplot2)
library(dplyr)

p = DotPlot(sce_cca, features = markers)
dat <- p$data

#获取cluster注释
anno <- distinct(df, sce_cca$seurat_clusters,sce_cca$celltype)
colnames(anno) <- c("id","celltype")
df <- left_join(dat, anno, by = "id")


cluster.order <- c(2,4,5,6,8,15,16,18,0,1,3,22,11,12,9,7,10,21,14,13,17,19,20)
dat$id <- factor(dat$id, levels= cluster.order)
colnames(dat)
# [1] "avg.exp"        "pct.exp"        "features.plot"  "id"            
# [5] "avg.exp.scaled"

ggplot正常气泡图：

ggplot(dat, aes(features.plot, id,size=pct.exp, fill=avg.exp.scaled)) + 
  geom_point(shape = 21, colour="black", stroke=0.5) +
  guides(size=guide_legend(override.aes=list(shape=21, colour="black", fill=NA))) + 
  theme(
    panel.background = element_blank(),
    panel.border = element_rect(fill = NA),
    panel.grid.major.x = element_line(color = "grey80"),
    panel.grid.major.y = element_line(color = "grey80"),
    axis.title = element_blank(),
    axis.text.y = element_text(color='black',size=12),
    axis.text.x = element_text(color='black',size=12, angle = 90, hjust = 1, vjust = 0.5))+
  scale_fill_gradientn(colours = c('#5749a0', '#0f7ab0', '#00bbb1',
                                    '#bef0b0', '#fdf4af', '#f9b64b',
                                    '#ec840e', '#ca443d', '#a51a49'))

image.png

#plot2 结合celltype与cluster
p = ggplot(df, aes(features.plot, interaction(id, celltype),size=pct.exp, fill=avg.exp.scaled)) + 
  geom_point(shape = 21, colour="black", stroke=0.5) +
  theme(
    panel.background = element_blank(),
    panel.border = element_rect(fill = NA),
    panel.grid.major.x = element_line(color = "grey80"),
    panel.grid.major.y = element_line(color = "grey80"),
    axis.title = element_blank(),
    axis.text.y = element_text(color='black',size=12),
    axis.text.x = element_text(color='black',size=12, angle = 90, hjust = 1, vjust = 0.5))+
  scale_fill_gradientn(colours = c('#5749a0', '#0f7ab0', '#00bbb1',
                                   '#bef0b0', '#fdf4af', '#f9b64b',
                                   '#ec840e', '#ca443d', '#a51a49'))+
  guides(y = "axis_nested")

image.png

#添加注释\把celltype颜色标记，与UMAP对应一致即可
p+theme(ggh4x.axis.nesttext.y = element_text(colour = c('#E58606', '#5D69B1', '#52BCA3', '#99C945', '#CC61B0', '#24796C', '#DAA51B',
                                                        '#2F8AC4', '#764E9F', '#ED645A', '#CC3A8E')),
        ggh4x.axis.nestline.y = element_line(size=2))

image.png

#当然，我们也可以直接标注线条,与UMAP对应一致即可
p+theme(ggh4x.axis.nestline.y = element_line(size=1,
                                             colour = c('#E58606', '#5D69B1', '#52BCA3', '#99C945', '#CC61B0', '#24796C', '#DAA51B',
                                                        '#2F8AC4', '#764E9F', '#ED645A', '#CC3A8E')))

image.png

完美，非常满意，觉得分享有用的点个赞再走呗！