火山图 加标签 不遮蔽 R pheatmap

火山图 加标签 不遮蔽 R pheatmap

library(ggplot2)


#head(data) #查看数据类型，主要有P值，Fold change和基因ID即可。
inputFile="D:\\GZlab_W_AQY\\实验记录\\原始数据\\Pvalue_234\\p234.csv" 


logFCfilter=0.8               #logFC过滤阈值
fdrFilter=0.1              #矫正后p值阈值ֵ

#setwd("D:\\Coding\\R_gzlab_docu\\PurchasefWeb\\111bioR\\19.vol")      #设置工作目录

cut_off_pvalue = 0.1

#读取文件
rt=read.table(inputFile,sep=",",header=T,check.names=F,row.names = 1)
head(rt)
head(rt$logFC)

#定义显著性
#Significant=ifelse((rt$fdr<fdrFilter & abs(rt$logFC)>logFCfilter), ifelse(rt$logFC>logFCfilter,"Up","Down"), "Not")
Significant=ifelse((rt$pvalue<fdrFilter & abs(rt$logFC)>logFCfilter), ifelse(rt$logFC>logFCfilter,"Up","Down"), "Not")


# 1. 颜色区分上下调，加辅助线
#绘制火山图
p = ggplot(rt, aes(logFC, -log10(pvalue)))+
  geom_point(aes(col=Significant))+
  scale_color_manual(values=c("green", "black", "red"))+
  labs(title = " ")+
  
  # 辅助线
  geom_vline(xintercept=c(-1,1),lty=4,col="black",lwd=0.8) +
  geom_hline(yintercept = -log10(cut_off_pvalue),lty=4,col="black",lwd=0.8) +
  
  
  theme(plot.title = element_text(size = 16, hjust = 0.5, face = "bold"))
p=p+theme_bw()
p



# 2. 画简单全黑 散点
ggplot(data = rt, aes(x = logFC, y = -log10(pvalue))) +
  geom_point(alpha=0.8, size = 1)



# 3. 颜色区分上下调，加FDR FC 辅助线
# 给数据加一列，上下调
data <- rt
data$change <- as.factor(ifelse(data$pvalue < 0.1 & abs(data$logFC) > 0.8,ifelse(data$logFC > 0.1,'UP','DOWN'),'NOT')) 
head(data)

ggplot(data = data, aes(x = logFC, y = -log10(pvalue), color = change)) +
  geom_point(alpha=0.8, size = 1) +
  theme_bw(base_size = 15) +
  theme(
    panel.grid.minor = element_blank(),
    panel.grid.major = element_blank()
  ) + 
  geom_hline(yintercept=2 ,linetype=4) + 
  geom_vline(xintercept=c(-1,1) ,linetype=4 ) +
  scale_color_manual(name = "", values = c("red", "green", "black"), limits = c("UP", "DOWN", "NOT"))   


# 4. 另外 加上标签


data$sign <- ifelse(data$fdr < 0.1 & abs(data$logFC) > 0.1,rownames(data),NA)

ggplot(data = data, aes(x = logFC, y = -log10(fdr), color = change)) +
  geom_point(alpha=0.8, size = 1) +
  theme_bw(base_size = 15) +
  theme(
    panel.grid.minor = element_blank(),
    panel.grid.major = element_blank()
  ) + 
  geom_hline(yintercept=2 ,linetype=4) + 
  geom_vline(xintercept=c(-1,1) ,linetype=4 ) +
  scale_color_manual(name = "", values = c("red", "green", "black"), limits = c("UP", "DOWN", "NOT")) +
  geom_text(aes(label = sign), size = 3)  


#4-2
data$sign <- ifelse(data$pvalue < 0.1 & abs(data$logFC) > 0.5,rownames(data),NA)

ggplot(data = data, aes(x = logFC, y = -log10(pvalue), color = change)) +
  geom_point(alpha=0.8, size = 1) +
  theme_bw(base_size = 15) +
  theme(
    panel.grid.minor = element_blank(),
    panel.grid.major = element_blank()
  ) + 
  geom_hline(yintercept=2 ,linetype=4) + 
  geom_vline(xintercept=c(-1,1) ,linetype=4 ) +
  scale_color_manual(name = "", values = c("red", "green", "black"), limits = c("UP", "DOWN", "NOT")) +
  geom_text(aes(label = sign), size = 3) 



# 5. 标签防遮蔽


data$sign2 <- ifelse(data$fdr < 0.005 & abs(data$logFC) > 2.5,rownames(data),NA)
data$sign2 <- ifelse(data$pvalue < 0.2 & data$logFC > 0.2,rownames(data),NA)

data$change <- as.factor(ifelse(data$pvalue < 0.2 & abs(data$logFC) > 0.2,ifelse(data$logFC > 0,'UP','DOWN'),'NOT')) 
head(data)
head(data)
library(ggrepel)
ggplot(data = data, aes(x = logFC, y = -log10(pvalue), color = change)) +
  geom_point(alpha=0.8, size = 2) +
  theme_bw(base_size = 16) +
  scale_x_continuous(limits = c(-4, 4))+
  scale_y_continuous(limits = c(0, 5))+
  theme(
    panel.grid.minor = element_blank(),
    panel.grid.major = element_blank()
  ) +
  
  scale_color_manual(name = "", values = c("red", "green", "black"), limits = c("UP", "DOWN", "NOT")) +
  geom_label_repel(aes(label=sign2), xlim=c(1.2, NA),segment.alpha=0.5,
                   size=4,max.overlaps=80 ,fontface="bold", color="#A0522D", box.padding=unit(0.35, "lines"), point.padding=unit(0.5, "lines"), 
                   segment.colour = "grey50",segment.size=0.1,fill = alpha(c("white"),0.1)) 
  #geom_label_repel(aes(label=sign2), xlim=c(1.5, NA),
         #          size=1,max.overlaps=50 ,fontface="bold", color="red", box.padding=unit(0.35, "lines"), point.padding=unit(0.5, "lines"), 
              #     segment.colour = "grey50",segment.size=0.1) 
#geom_text_repel(aes(label = sign), box.padding = unit(0.3, "lines"), point.padding = unit(0.4, "lines"), show.legend = F, size = 3)



# 6. 感兴趣的基因标出来

#读取文件
inputFile = "input2.txt"
data2=read.table(inputFile,sep="\t",header=T,check.names=F)

#data$LABEL <- list(1,3,5, 123, 567)
data2$change <- as.factor(ifelse(data$fdr < 0.01 & abs(data$logFC) > 1,ifelse(data$logFC > 1,'UP','DOWN'),'NOT')) 

ggplot(data = data2, aes(x = logFC, y = -log10(fdr), color = change)) +
  geom_point(alpha=0.8, size = 2) +
  theme_bw(base_size = 15) +
  theme(
    panel.grid.minor = element_blank(),
    panel.grid.major = element_blank()
  ) +
  scale_color_manual(name = "", values = c("red", "green", "black"), limits = c("UP", "DOWN", "NOT")) +
  geom_label_repel(aes(label=LABEL), fontface="bold", color="grey50", box.padding=unit(0.35, "lines"), point.padding=unit(0.5, "lines"), segment.colour = "grey50")



# 7.  可互动图

library(plotly)
p <- plot_ly(data, 
             x = ~logFC, 
             y = ~-log10(pvalue), 
             text = ~sign2, 
             type = 'scatter', 
             mode = 'markers'
)
p