#先准备好R包if(!require(ggplot2)) install.packages("ggplot2")if(!require(ggrepel)) install.packages("ggrepel")if(!require(dplyr))install.packages("dplyr")library(ggplot2)library(ggrepel)library(dplyr)

#本次我们有3种方可以实现散点添加标签#方法一：利用空字符“”#这种方法是参照帮助文档里的一段代码：#下面代码来源于geom_text_repel的帮助文档p <- ggplot(mtcars,aes(wt, mpg, label = rownames(mtcars), colour = factor(cyl))) +  geom_point()# Hide some of the labels, but repel from all data pointsmtcars$label <- rownames(mtcars)mtcars$label[1:15] <- ""p + geom_text_repel(data = mtcars, aes(wt, mpg, label = label))

#这是结果图，可以看到，一些点有标签名，一些没有#于是大海哥学以致用#先画出火山图p <- ggplot(data = data, aes(x = log2(data$FC),y = -log10(data$p.value),colour=change,label = data$symbol)) +geom_point(alpha=0.4, size=3.5) + scale_color_manual(values=c("blue", "grey","red"))+xlim(c(-4.5, 4.5)) +geom_vline(xintercept=c(-1,1),lty=4,col="black",lwd=0.8) +geom_hline(yintercept = -log10(0.000001),lty=4,col="black",lwd=0.8) +labs(x="log2(fold change)",y="-log10 (p-value)",title="Differential metabolites") +theme_bw()+ theme(plot.title = element_text(hjust = 0.5), legend.position="right",legend.title = element_blank())p

#然后我们可以筛选出部分基因#想在图上做修改，一半是调参数，一半是调数据。我们现在要做的就是调数据：要标记的，label=基因，无需标记的，label=“”。data$label=ifelse(data$p.value < 0.000001 & abs(log2(data$FC)) >= 1,data$symbol,"")#这就好了，然后把文字图层叠加上去#data为差异分析结果，大家自行修改哦！包含FC列和p.value以及基因名列就可以啦！p+geom_text_repel(data = data, aes(x = log2(data$FC), y = -log10(data$p.value), label = label),size = 3,box.padding = unit(0.5, "lines"),point.padding = unit(0.8, "lines"),segment.color = "black",show.legend = FALSE)

##完美实现！但是这种办法只适用于数据量较小的时候，数据量太大了对于设备的性能要求就会要求太高了！#方法二：图层叠加#这个方法是来自R数据科学笔记best_in_class <- mpg %>%  group_by(class) %>%  filter(row_number(desc(hwy)) == 1)ggplot(mpg, aes(displ, hwy)) +  geom_point(aes(color = class)) +  geom_point(size = 3, shape = 1, data = best_in_class) +  ggrepel::geom_label_repel(    aes(label = model),    data = best_in_class  )

#这个方法适用于较大数据#先同样画出火山图p <- ggplot(data = test,aes(x = logFC,y = P.value)) +  #test是差异分析结果，大家自行更换哦，包含logFC列和P.value以及基因名列就可以啦！geom_point(alpha=0.4, size=3.5,aes(color=change)) +scale_color_manual(values=c("blue", "grey","red"))+geom_vline(xintercept=c(-1,1),lty=4,col="black",lwd=0.8) +geom_hline(yintercept = -log10(0.01),lty=4,col="black",lwd=0.8) +theme_bw()p

#然后选择想标记的基因，新建一个标签图层for_label <- test %>%   filter(abs(logFC) >4& P.value> -log10(0.000001))#再把标签图层叠加上去p +  geom_point(size = 3, shape = 1, data = for_label) +ggrepel::geom_label_repel(aes(label = symbol),data = for_label,    color="black"  )

#还有方法三，也是最便捷的一种方式，因为ggpubr的函数有现成的参数library(ggpubr) colnames(test)[4] <- "v"ggscatter(test,x = "logFC",y ="P.value", ylab="-log10(P.value)",size=0.5,color = "change", palette = c("#00AFBB", "#999999", "#FC4E07"))#然后可以手动选择我们想要标记的基因，这里大海哥列举了这几个"CD36", "DUSP6", "DCT", "SPRY2", "MOXD1", "ETV4"，大家自行修改。ggscatter(test, x = "logFC", y = "v", ylab="-log10(P.value)", color = "change", size = 0.5, label = "symbol", repel = T, palette = c("#00AFBB", "#999999", "#FC4E07") , 
#就是这个label.select标签，直接加上去就行。#label.select = dat$symbol[1:30] , label.select = c("CD36", "DUSP6", "DCT", "SPRY2", "MOXD1", "ETV4" ) )#先看看原始的图

#看看加上后的图，我们这里重新选择logFC前30个基因ggscatter(test,x = "logFC",y = "v",ylab="-log10(P.value)",color = "change",size = 0.5,label = "symbol",repel = T,palette = c("#00AFBB", "#999999", "#FC4E07") ,label.select = test$symbol[1:30])