桑基图+气泡图展示富集分析结果

有小伙伴发了一张图，是关于富集分析的，只不过展示和我们之前的不太一样，是桑基图+气泡图的形式，特点就是GO terms和其对应的关键基因用桑基图展示，GO结果用气泡图展示。这幅图在很多在线生信工具中都有，很方便就能完成。本来是不想做了，但是很巧，又在别的文献中看到了，所以做一下，还是比较新奇的，至少我是第一次见。桑基图+气泡图组合，最后修饰一下即可。

参考链接：https://mp.weixin.qq.com/s?__biz=Mzg5OTYzMzY5Ng==&mid=2247488144&idx=1&sn=f52d4f6b876f7408a6bf01bda8ea58eb&chksm=c05115dff7269cc9699d8a5d1909aa57ee29efb06cf0c65be7a80fe6b3e34b43e5344fd7cec1&token=532010673&lang=zh_CN#rd

setwd("D:/KS项目/公众号文章/桑基图结合富集分析图")
library(tidyverse)
# devtools::install_github("davidsjoberg/ggsankey")
library(ggsankey)
library(ggplot2)
install.packages("cols4all")
library(cols4all)

先做桑基图，作图数据的话是我们GO富集的结果，自己整理数据，至于每个Trems展示的基因可以选择对自己研究展示关键的基因。

df <- read.csv("df.csv", header = T)
df1 <- df[,-1]
colnames(df1)
df1_trans <- df1 %>%make_long(gene, pathway)
df1_trans$node <- factor(df1_trans$node,levels = c(df1$pathway %>% unique()%>% rev(),
                                     df1$gene %>% unique() %>% rev()))

colnames(df1_trans)
ggplot(df1_trans, aes(x = x,
                      next_x= next_x,
                      node= node,
                      next_node= next_node,
                      fill= node,
                      label= node)) +
  geom_sankey(flow.fill="#DFDFDF",
              flow.color="grey60",
              node.fill=dittoColors()[1:44],
              width=0.15) + 
  geom_sankey_text(size = 3,
                   color= "black",
                   hjust=1) + 
  theme_void()

修饰一下：关键通路可以标注出来。

p1 = ggplot(df1_trans, aes(x = x,
                      next_x= next_x,
                      node= node,
                      next_node= next_node,
                      fill= node,
                      label= node)) +
  geom_sankey(flow.fill="#DFDFDF",
              flow.color="grey60",
              node.fill=dittoColors()[1:44],
              width=0.15) + 
  geom_sankey_text(size = 3,
                   color= c(rep("black",30),"red","red",rep("black",12)),
                   hjust=1) + 
  theme_void()

假设是KEGG的话，可以展示多级分类：

#展示通路
df2 <- df[,-2]
df2_trans <- df2 %>%make_long(sub_path, pathway)
#作图
ggplot(df2_trans, aes(x = x,
                      next_x= next_x,
                      node= node,
                      next_node= next_node,
                      fill= node,
                      label= node)) +
  scale_fill_manual(values = dittoColors())+
  geom_sankey(width=0.15) + #node的宽度
  geom_sankey_text(size = 3,
                   color= "black") + 
  theme_void()+
  theme(legend.position = "none")

接下来，做一个气泡图，这个很简单了：

enrich <- read.csv("Enrichment.csv", header = T)
colnames(enrich)
enrich$Log.q.value. <- -enrich$Log.q.value.
enrich$Description <- factor(enrich$Description, levels = enrich$Description %>% rev())

p2  = ggplot(enrich, aes(Generatio, Description, color=Log.q.value.))+
  geom_point(aes(size=Count))+
  scale_color_gradient(low='#14B3FF',high='#E42A2A',name = "-Log(q-value)")+
  theme_bw()+
  theme(axis.title.y = element_blank(),
        axis.text.y = element_blank(),
        axis.ticks.y = element_blank(),
        axis.text.x = element_text(colour = 'black',size = 10),
        axis.title.x = element_text(colour = 'black',size = 12),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank())

最后结合二者，用AI修饰一下就达到效果了。觉得分享有的点个赞再走呗！