ggplot2优雅绘制相关性网络热图(批量修改字符)

R语言数据分析指南

发布于 2024-07-02 16:15:35

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❝本节来介绍如何使用R绘制相关性网络热图，此图之前已经做过很多次介绍，本次主要介绍如何批量转换特殊化学字符进行绘图。图形数据为随意构建无实际意义，整个过程仅供参考。

结果图

图形解读

❝此图作为常见的相关性网络热图已经有很多案例介绍了，此次主要通过自定义函数来批量转换化学表达式来使其正确在图中展示。

加载R包

library(tidyverse)
library(RColorBrewer)
library(ggtext)
library(magrittr)
library(reshape)
library(psych)
library(linkET)

数据清洗

varechem <- read_tsv("varechem.xls") %>% column_to_rownames(var="id") %>% 
  set_colnames(c("NH4+", "CaSO4", "H2O", "C6H12O6", "CH3COOH","H2SO4", 
                 "KNO3", "Mg(OH)2", "Fe2O3",
                 "Al3+", "SO4^2-", "NO3-", "CO3^2-", "PO4^3-"))

table1 <- varechem %>% rownames_to_column(var="id") %>% 
  pivot_longer(-id) %>% 
  c_html(.,"name") %>% 
  pivot_wider(values_from = value) %>% 
  column_to_rownames(var="id")

数据整合

table2 <- read_tsv("varespec.xls") %>% column_to_rownames(var="id") %>% select(1:20)

mantel <- mantel_test(table2, table1,
            spec_select = list(Spec01 = 1:7,
                               Spec02 = 8:18,
                               Spec03 = 19:20)) %>% 
  mutate(rd = cut(r, breaks = c(-Inf, 0.2, 0.4, Inf),
                  labels = c("< 0.2", "0.2 - 0.4", ">= 0.4")),
         pd = cut(p, breaks = c(-Inf, 0.01, 0.05, Inf),
                  labels = c("< 0.01", "0.01 - 0.05", ">= 0.05")))

绘制热图

qcorrplot(correlate(table1,method = "pearson"),diag=F,type="lower")+
  geom_tile()+
  geom_mark(size=2.5,sig.thres=0.05,sep="\n")+
  geom_couple(aes(colour=pd,size=rd),data=mantel,label.colour = "black",
              curvature=nice_curvature(0.15),
              nudge_x=0.2,
              label.fontface=2,
              label.size =4,
              drop = T)+
  scale_fill_gradientn(colours = RColorBrewer::brewer.pal(11,"RdBu"))+
  scale_size_manual(values = c(0.5, 1, 2)) +
  scale_colour_manual(values =c("#D95F02","#1B9E77","#A2A2A288")) +
  guides(size = guide_legend(title = "Mantel's r",override.aes = list(colour = "grey35"), order = 2),
         colour = guide_legend(title = "Mantel's p",override.aes = list(size = 3), order = 1),
         fill = guide_colorbar(title = "pearson's r",order = 3))+
  theme(plot.margin = unit(c(0,0,0,1),units="cm"),
        legend.background=element_blank(),
        legend.key = element_blank(),
        axis.text=element_markdown(color="black",size=8))

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原始发表：2024-06-28，如有侵权请联系 cloudcommunity@tencent.com 删除

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