复现nature medicine图表：pheatmap结合gg

今天复现一篇Nature medicine文章的图表，图大家都很熟悉了，气泡图+聚类，这类图我们在ggplot做热图的时候我们以后实现过了：热图5：ggplot2画热图及个性化修饰。但是为什么这里要复现，不是炒冷饭，肯定是有新东西嘛，不然怎么拿的出手呢？本文作者提供了部分数据和部分代码，他这个图是先用pheatmap做了一个聚类热图，然后利用热图的聚类使用ggplot做的气泡图，最后用AI或者PS修饰组合在一起。其实很多小伙伴觉得在ggplot做聚类不太顺手的话，可以借鉴这个思路，很不错。

image.png

（Longitudinal dynamics of clonal hematopoiesis identifies gene-specific fitness effects）第一步，我们先做一个聚类热图：

setwd('D:/KS项目/公众号文章/pheatmap和ggplot的结合')
df <- read.csv('df.csv', header = T)
data <- df[df$PreferredSymbol %in% c("DNMT3A", "TET2", "NOTCH1", "JAK2", "U2AF2", "JAK3", "ASXL1"), ]
data1 <- data[, c("Participant_ID","Largest_VAF","wave","PreferredSymbol")]

#行注释
data.anno <- data1[ , colnames(data1) %in% c("wave", "Participant_ID")]
data.anno <- unique(data.anno)
rownames(data.anno) <- data.anno$Participant_ID


for_order <- reshape2::dcast(as.data.frame(data1),
                             PreferredSymbol~Participant_ID, value.var="Largest_VAF")
for_order[is.na(for_order)] = 0
rownames(for_order) <- for_order$PreferredSymbol
for_order <- for_order[ , !(colnames(for_order) %in% c("PreferredSymbol")) ]
cluster_order <- pheatmap(for_order, annotation_col = data.anno, 
                          show_rownames = F, show_colnames = F,
                          annotation_names_col = F)

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第二步，做一个气泡图，气泡图的行列排序和热图一样。

#气泡图

p <- ggplot(data, aes(Participant_ID, PreferredSymbol))+
  geom_point(aes(size = Largest_VAF,colour = Variant_Classification), alpha=0.3)+
  scale_size(range = c(0,15)) +
  xlab("") + 
  ylab("")+theme_minimal() + 
  theme(panel.background = element_blank(), axis.line = element_line(colour = "black"),
                                 legend.text=element_text(size=11),
        axis.text.x = element_blank(),
        axis.text.y = element_text(color="black", size=9),
        axis.text=element_text(size=16),
        axis.title=element_text(size=16, face = "bold"))+
  scale_y_discrete(limits=rev(cluster_order$tree_row$labels[cluster_order$tree_row$order]))+
  scale_x_discrete(limits=(cluster_order$tree_col$labels[cluster_order$tree_col$order]))+
  guides(colour = guide_legend(override.aes = list(size=5), 
                               title = c("Variant Classification")),
         size = guide_legend(title = c("VAF")))+
  scale_colour_manual(values=c(Frame_Shift_Del="#00BBDA",
                               Frame_Shift_Ins="#E18A00",
                               Missense_Mutation="#BE9C00",
                               Nonsense_Mutation="#24B700",
                               Splice_Region="#00C1AB",
                               Splice_Site="#F8766D"))

image.png

然后两个修饰组合一下就可以了。觉得分享对你有用的点个赞再走呗！