R优雅的自定义绘制代谢通路图

R语言数据分析指南

发布于 2022-12-20 11:58:14

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代码可运行

❝最近看到一个非常好的案例来分享一下，使用igraph，ggraph等R包来自定义绘制代谢通路pathway，原文文档链接见下方，数据可自行去官网下载。代码过程很是简洁，当然难点也许在于构建边文件与点文件。这需要各位观众老爷细细品味 ❞

原文文档

❝https://github.com/cxli233/ggpathway❞

加载R包

library(tidyverse)
library(igraph)
library(ggraph)
library(readxl)
library(viridis)
library(RColorBrewer)
library(rcartocolor)

构建边数据

example1_edge_table <- tribble(
  ~from, ~to,  ~label,
  "Glc6P", "6P-gluconolactone",  "Glc6PHD",
  "6P-gluconolactone", "6P-glucoconate",  "6P-gluconolactonase",
  "6P-glucoconate", "Ru5P", "6P-gluconateDH"
)
# 构建点数据
example1_nodes_table <- tribble(
  ~name, ~x,  ~y,
  "Glc6P", 1, 0,
  "6P-gluconolactone", 2, 0,  
  "6P-glucoconate", 3, 0,
  "Ru5P", 4, 0
)

文件整合

example1_network <- graph_from_data_frame(
  d = example1_edge_table,
  vertices = example1_nodes_table,
  directed = T
)

绘制基础通路图

ggraph(example1_network, layout = "manual", 
       x = x, y = y) +
  geom_node_text(aes(label = name), hjust = 0.5) +
  geom_edge_link(aes(label = example1_edge_table$label), 
                 angle_calc = 'along',
                 label_dodge = unit(2, 'lines'),
                 arrow = arrow(length = unit(0.5, 'lines')), 
                 start_cap = circle(4, 'lines'),
                 end_cap = circle(4, 'lines')) +
  theme_void()

绘制PPP代谢途径

导入数据

example2_edges <- read_excel("OPPP_edges.xlsx")
example2_nodes <- read_excel("OPPP_nodes.xlsx")

构建新标签

example2_nodes <- example2_nodes %>% 
  mutate(label = str_remove(name, "_\\d"))

文件整合

example2_network <- graph_from_data_frame(
  d = example2_edges,
  vertices = example2_nodes,
  directed = T)

绘制PPP代谢途径图

ggraph(example2_network, layout = "kk") +
  geom_node_point(size = 3, aes(fill = as.factor(carbons)), 
                  alpha = 0.8, shape = 21, color = "grey20") +
  geom_node_text(aes(label = label), hjust = 0.5, repel = T) +
  geom_edge_link(label_dodge = unit(2, 'lines'),
    arrow = arrow(length = unit(0.4, 'lines')), 
    start_cap = circle(1, 'lines'),
    end_cap = circle(2, 'lines')) +
  scale_fill_manual(values = carto_pal(7, "Vivid")) +
  labs(fill = "Carbons") +
  theme_void()

TCA途径

导入数据

example3_edges <- read_excel("TCA_cycle_edges.xlsx")
example3_nodes <- read_excel("TCA_cycle_nodes.xlsx")

构建标签文本

example3_nodes <- example3_nodes %>% 
  mutate(label = str_remove(name, "_\\d"))

整合数据

example3_network <- graph_from_data_frame(
  d = example3_edges,
  vertices = example3_nodes,
  directed = T)

绘制TCA途径图

ggraph(example3_network, layout = "manual",
       x = x, y = y) +
  geom_node_point(size = 3, aes(fill = as.factor(carbons)), 
                  alpha = 0.8, shape = 21, color = "black") +
  geom_edge_link(arrow = arrow(length = unit(0.4, 'lines')), 
                 start_cap = circle(0.5, 'lines'),
                 end_cap = circle(0.5, 'lines'), 
                 width = 1.1, alpha = 0.5) +
  geom_node_text(aes(label = label), hjust = 0.5, repel = T) +
  annotate(geom = "text", label = "TCA Cycle", 
           x = 0, y = 0, size = 5, fontface = "bold") +
  scale_fill_manual(values = carto_pal(7, "Vivid")) +
  labs(fill = "Carbons") +
  theme_void() +
  coord_fixed()