大傢好，我是半島小鐵盒！上期內容分享了如何使用python來繪制火山圖，本期內容為大傢分享的是如何使用R語言的ggplot2繪制好看的火山圖。往下看，三分鐘教會你！

1.加載繪圖數據

導包，加載基因差異表達數據，重定義列名：

library(ggplot2)
library(tidyverse)
library(ggrepel)
library(latex2exp)
library(RColorBrewer)
# 讀取rawdata
deg_data <- read.csv('https://raw.githubusercontent.com/jiangtao639/ExampleDataRepository/master/volcano_data.csv',
                 header=TRUE, row.names = 1)
# 修改列名
data <- deg_data[c('row', 'log2FoldChange', 'pvalue', 'padj')]
colnames(data) <- c('geneName', 'log2FoldChange', 
                    'pvalue', 'FDR')

2.數據預處理

分別設置差異倍數和顯著性的閾值為2和0.5，添加差異表達水平標簽

log2FC_tresh <-  1
FDR_tresh <-  0.05
# 添加差異表達水平標簽， 按照FDR升序
data <- data %>% mutate(data, label = 
          ifelse(log2FoldChange >= log2FC_tresh & FDR < FDR_tresh, 'Up',
          ifelse(log2FoldChange <= -log2FC_tresh & FDR < FDR_tresh, 'Down', 
          'Normal'))) %>%
           arrange(FDR)

添加要註釋的核心基因

# 這裡註釋前10個
data$annotation <- ''
data[1:10, c("annotation")] <- data[1:10, c("geneName")]

view(data)

3.基礎繪圖

最樸素的繪圖，什麼參數都不調整。感覺都比seaborn畫的好看

p1 <- ggplot(data=data, mapping=aes(x=log2FoldChange, y=-log10(FDR)))  
  geom_point(mapping=aes(color=label, fill=label), 
              alpha=0.8, size=1, shape=21)  
  geom_vline(xintercept = c(-log2FC_tresh,log2FC_tresh), 
             linetype ="dashed")  
  geom_hline(yintercept = -log10(FDR_tresh), 
             linetype ="dashed")  
  theme_bw()

4.參數細調的精美繪圖

主要調整下坐標軸標簽、圖例位置和字體以及背景， 添加核心基因註釋

p2 <- p1  
  geom_text_repel(aes(label=annotation, color=label), size=3, 
                  max.overlaps = 100, 
                  key_glyph = draw_key_point)  
  labs(x= TeX("$Log_2 \\textit{FC} $"),
       y= TeX("$-Log_{10} \\textit{FDR} $"),
       title="VolcanoPlot")  
  theme(plot.title = element_text(hjust=0.5, size=15),
        plot.background = element_rect(fill = "white", 
        color = "black"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        legend.position = c(0.99, 0.99),
        legend.justification = c(1, 1),
        legend.background = element_rect(fill = "white", 
        color = "grey"),
        legend.title = element_text(size=15, hjust=0.5),
        legend.text = element_text(size = 12),
  )  
  guides(color=guide_legend("Level"),
         fill=guide_legend("Level"))

是不是更好看了！

修改配色

p3 <- p2    
  scale_fill_manual(values=c("#00AFBB","#999999","#FC4E07"))  
  scale_color_manual(values=c("#00AFBB","#999999","#FC4E07"))
p4 <- p2   
  scale_fill_brewer(palette = "Set1")  
  scale_color_brewer(palette = "Set1")

5.繪制漸變火山圖

# 漸變火山圖
p <- ggplot(data=data, mapping=aes(x=log2FoldChange, y=-log10(FDR)))  
  geom_point(mapping=aes(color=-log10(FDR), fill=-log10(FDR), size=-log10(FDR)), alpha=0.8, shape=21)  
  scale_size_continuous(range=c(1,4))  
  geom_text_repel(aes(label=annotation, color=-log10(FDR)), size=3, 
                  max.overlaps = 100, key_glyph = draw_key_point)  
  geom_vline(xintercept = c(-log2FC_tresh,log2FC_tresh), linetype ="dashed")  
  geom_hline(yintercept = -log10(FDR_tresh), linetype ="dashed")  
  labs(x= TeX("$Log_2 \\textit{FC} $"),
       y= TeX("$-Log_{10} \\textit{FDR} $"),
       title="VolcanoPlot")   
  theme_bw()   
  theme(plot.title = element_text(hjust=0.5, size=15),
        plot.background = element_rect(fill = "white", color = "black"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        legend.position = c(0.99, 0.49),
        legend.justification = c(1, 0.5),
        legend.background = element_rect(fill = "white"),
        legend.title = element_text(size=12, hjust=0.5),
        legend.text = element_text(size = 12),
  )   
  guides(fill=guide_colorbar(TeX("$-Log_{10} \\textit{FDR} $")),
         color='none', size='none')
p1 <- p   scale_fill_gradientn(values = seq(0,1,0.2),
                       colors = c("#39489f","#39bbec","#f9ed36","#f38466","#b81f25")) 
  scale_color_gradientn(values = seq(0,1,0.2),
                        colors = c("#17194e","#68bfe7","#f9ed36","#a22f27","#211f1f"))

修改配色主題

p2 <- p    scale_fill_gradientn(values = seq(0,1,0.2),
                                colors = rev(brewer.pal(8, "Spectral"))) 
  scale_color_gradientn(values = seq(0,1,0.2),
                        colors = rev(brewer.pal(8, "Spectral")))
p2

總結 >>>

R語言繪圖實現起來要比python容易，強烈推薦使用ggplot2作為底層庫來繪圖，繪制的圖案更加符合美學！火山圖完結~