Shengxin commonly used analysis graphics drawing 02 -- unlock the essence of volcano map!

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With R The basis of language , as well as ggplot2 Basis of drawing , our 「 Students often use analysis graphics 」 The drawing of can be put on the agenda ！ This series , Elder martial brother began to take everyone to learn how to use R Language draw our own various analysis charts ！

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Because all the analysis codes in this series are carefully sorted and commented by elder martial brother ！ Welcome to thumb up 、 Collection 、 forward ！

Your support is the biggest driving force for me to continuously update ！

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Sample data and code acquisition

The series includes ：

• Have you learned all kinds of heat maps ？

  • General heat map
  • Annular heat map
• Unlock the essence of volcano map ！

  • plot Function can draw volcano map ？
  • High level function to draw volcano map --ggplot2、ggpurb
• Classic enrichment analysis and Bubble Diagram 、 Histogram drawing

  • Bubble plot
  • Histogram drawing
• Enrichment analysis circle diagram
• Enrichment analysis chord
• Draw a Sankey map that can impress reviewers
• Survival analysis -- KM diagram
• Basics PCA chart
• Clouds and rain
• Wayne Tu
• Ring interaction network diagram
• Interaction network diagram
• Cluster tree beautification
• Enrichment analysis bubble chart advanced version
• mantel test Correlation chart
• Clouds of words
• Waterfall Plot
• Forest map
• Manhattan
• Dumbbell chart
• Three wire table
• Nested circle graph
• Nomogram
• Bee colony diagram
• boxplot + Bessel curve
• Matrix scatter
• wait , Think of adding more ！！！

The effect of volcano map in this issue is displayed

Effect display

R Built-in function plot Can draw a volcanic map ？

##############
data <- read.csv("DEG.csv",row.names = 1)

color <- rep("#999999",nrow(data))

color[data$pvalue <0.05 & data$log2FoldChange > 1] <- "#FC4E07"
color[data$pvalue <0.05 & data$log2FoldChange < -1] <- "#00AFBB"

par(oma = c(0,2,0,0))

plot(data$log2FoldChange,-log10(data$pvalue),pch = 16,cex = 0.5,
     xlim = c(-4,4), ylim = c(0,32), col = color, frame.plot = F,
     xlab = "log2FC", ylab = "-log10(Pvalue)", cex.axis = 1, cex.lab = 1.3)

#  Add Guides ：
abline(h = -log10(0.05),lwd = 2, lty = 3)  # lwd Set the width of the line ,lty Set the type of line ;
abline(v = c(-1,1),lwd = 2, lty = 3)  # lwd Set the width of the line ,lty Set the type of line ;

#  Add legend 
legend(x = 3, y = 32, legend = c("Up","Normal","Down"), 
       bty = "n", #  Remove the border 
       pch = 19,cex = 1, #  Set the style and size of the point 
       x.intersp = 0.3, #  Set the distance between words and points ;
       y.intersp = 0.3, #  Set the height difference between points , Equivalent to line spacing ;
       col = c("#FC4E07","#999999","#00AFBB"))

#  Add tags ：
color = c()
color[which(data[1:10,]$regulate == "Up")] = "#FC4E07"
color[which(data[1:10,]$regulate != "Up")] = "#00AFBB"
text(data$log2FoldChange[1:10],-log10(data$pvalue)[1:10],
     labels = data$row[1:10],
     adj = c(0,1.5),
     cex = 0.6,
     col = color)

• Encapsulate the above code into a function , Later call , You can map with one click ：

#  Wrapper functions ：
#  adjustment 1: xlim and ylim We have to get rid of 
#  adjustment 2:  Change the position of the legend 
plotVoc <- function(data){
  color <- rep("#999999",nrow(data))
  
  color[data$pvalue <0.05 & data$log2FoldChange > 1] <- "#FC4E07"
  color[data$pvalue <0.05 & data$log2FoldChange < -1] <- "#00AFBB"
  
  par(oma = c(0,2,0,0))
  
  plot(data$log2FoldChange,-log10(data$pvalue),pch = 16,cex = 0.5,
       col = color, frame.plot = F,
       xlab = "log2FC", ylab = "-log10(Pvalue)", cex.axis = 1, cex.lab = 1.3)
  
  #  Add Guides ：
  abline(h = -log10(0.05),lwd = 2, lty = 3)  # lwd Set the width of the line ,lty Set the type of line ;
  abline(v = c(-1,1),lwd = 2, lty = 3)  # lwd Set the width of the line ,lty Set the type of line ;
  
  #  Add legend 
  legend(x = 3, y = max(-log10(data$pvalue)), legend = c("Up","Normal","Down"), 
         bty = "n", #  Remove the border 
         pch = 19,cex = 1, #  Set the style and size of the point 
         x.intersp = 0.3, #  Set the distance between words and points ;
         y.intersp = 0.3, #  Set the height difference between points , Equivalent to line spacing ;
         col = c("#999999", "#FC4E07","#00AFBB"))
  
  #  Add tags ：
  color = c()
  color[which(data[1:10,]$regulate == "Up")] = "#FC4E07"
  color[which(data[1:10,]$regulate != "Up")] = "#00AFBB"
  text(data$log2FoldChange[1:10],-log10(data$pvalue)[1:10],
       labels = data$row[1:10],
       adj = c(0,1.5),
       cex = 0.6,
       col = color)
}


data <- read.csv("DEG2.csv",row.names = 1)

plotVoc(data)

effect 1

High level function to draw volcano map --ggplot2、ggpurb

• Use ggplot2 draw ：

library(ggplot2)

data <- read.csv("DEG.csv",row.names = 1)

#################
# ggplot2 Mapping volcanoes 
data$label <- c(rownames(data)[1:10],rep(NA,nrow(data) - 10))

ggplot(data,aes(log2FoldChange,-log10(pvalue),color = regulate)) + 
  xlab("log2FC") + 
  geom_point(size = 0.6) + 
  scale_color_manual(values=c("#00AFBB","#999999","#FC4E07")) + 
  geom_vline(xintercept = c(-1,1), linetype ="dashed") +
  geom_hline(yintercept = -log10(0.05), linetype ="dashed") + 
  theme(title = element_text(size = 15), text = element_text(size = 15)) + 
  theme_classic() + 
  geom_text(aes(label = label),size = 3, vjust = 1,hjust = -0.1)

• Use ggpurb Of scatter Functions can also be drawn ：

#############
#  Use ggpurb Mapping volcanoes ：
library(ggpubr)
data$pvalue <- -log10(data$pvalue)
ggscatter(data, 
          x = "log2FoldChange", 
          y = "pvalue", 
          ylab="-log10(P.value)", 
          size=0.6, 
          color = "regulate", 
          label = rownames(data),
          label.select = rownames(data)[1:10],
          repel = T,
          palette = c("#00AFBB", "#999999", "#FC4E07")) +
          geom_hline(yintercept = 1.30,linetype ="dashed") +
          geom_vline(xintercept = c(-1,1),linetype ="dashed")

effect 2

Catalogue of previous excellent graphics

copying

The articles