没想到修个火山图这么麻烦 by 生信菜鸟团

看到了曾老师于20年布置的学徒作业~

就是需要复现上图~ 草草一看应该是提取原始数据，取差异基因然后绘图吧。

这个文章的补充材料里面给的是counts和P值...

先做了除法，就是两个实验组标准化counts分别除以除以对照组标准化counts

rm(list=ls())
options(warn = -1)
##结果发现人家可能只是用了除法
library(dplyr)
author.matrix=read.delim(file="nanostring_author_gene.txt", header = T,sep = "\t",quote = "\"",
                         row.names = 1)
colnames(author.matrix)
colnames(author.matrix)=c("Cont","STING.activated","STING.deficient","Cont.vs.activated_Pvalue","Cont.vs.deficient_Pvalue")
##添加除法列,判断谁除谁
author.matrix["Cdh5",] #"Cdh5""STING.activated"高表达，"STING.deficient"低表达
# Cont STING.activated STING.deficient Cont.vs.activated_Pvalue Cont.vs.deficient_Pvalue
# Cdh5 50.954         143.587          34.814                    0.045                    0.014
# Cont作为分母
author.matrix$de.vs.Cont=author.matrix$STING.deficient / author.matrix$Cont
author.matrix$acti.vs.Cont=author.matrix$STING.activated / author.matrix$Cont
author.matrix["Cdh5",]#检验一下
# Cont STING.activated STING.deficient Cont.vs.activated_Pvalue Cont.vs.deficient_Pvalue
# Cdh5 50.954         143.587          34.814                    0.045                    0.014
# de.vs.Cont acti.vs.Cont
# Cdh5  0.6832437     2.817973

9.2 整理矩阵

再把两部分数据结合，按照数据来源进行分组

##整理矩阵
draw.data=data.frame(gene=c(rownames(author.matrix),rownames(author.matrix)),
                     fold=c(author.matrix$acti.vs.Cont,author.matrix$de.vs.Cont),
                     p_value=c(author.matrix$Cont.vs.activated_Pvalue,
                               author.matrix$Cont.vs.deficient_Pvalue),
                     group=factor(c(rep(1,750),rep(2,750))))

draw.data[750:751,] # 核对
# gene      fold p_value group
# 750 Map2k2 1.0014670    0.98     1
# 751    Itk 0.6636043    0.19     2
 author.matrix[c(750,1),]
# Cont STING.activated STING.deficient Cont.vs.activated_Pvalue
# Map2k2 481.946         482.653         462.779                     0.98
# Itk      6.531          23.041           4.334                     0.00
# Cont.vs.deficient_Pvalue de.vs.Cont acti.vs.Cont
# Map2k2                    0.395  0.9602300     1.001467
# Itk                       0.190  0.6636043     3.527944
# draw.data$Pvalue_log10=log10(draw.data$p_value)
# draw.data=draw.data[-(1:10),]
# draw.data=draw.data[draw.data$Pvalue_log10 != "-Inf",]
# #save(draw.data,file = "drawdata.Rdata")

最后得到用于绘图的矩阵如下~找到图示基因与计算结果核对，发现能对的上。

10 绘图

10.1 先绘一张基础图

emmmm，外部链接难以复制到公众号内部，请有需要的各位自行检索

问了师弟在网上找了和这个图长的差不多的图像，

《MAplot转录组差异基因表达展示》

MAplot转录组差异基因表达展示_maplot r语言_TS的美梦的博客-CSDN博客自己也顺着这线索另外找了教程

《RNA-Seq分析中（二）——用R画带基因名标签的MA图》

RNA-Seq分析中（二）——用R画带基因名标签的MA图 - 知乎 (zhihu.com)另外

上面算是模板吧。

其实引起我最大注意的还是，看到横坐标是科学计数法显示的

于是就搜索的教程

《如何使用ggplot更改轴上数字的格式？》

如何使用ggplot更改轴上数字的格式？- 问答 - 腾讯云开发者社区-腾讯云 (tencent.com)发现作者给了个函数

#####科学记数法显示x轴坐标
 fancy_scientific <- function(l) {
   # turn in to character string in scientific notation
   l <- format(l, scientific = TRUE)
   l <- gsub("0e\\+00","0",l)
   # quote the part before the exponent to keep all the digits
   l <- gsub("^(.*)e", "'\\1'e", l)
   # remove "+" after exponent, if exists. E.g.: (3x10^+2 -> 3x10^2) 
   l <- gsub("e\\+","e",l)
   # turn the 'e+' into plotmath format
   l <- gsub("e", "%*%10^", l)
   # convert 1x10^ or 1.000x10^ -> 10^ 
   l <- gsub("\\'1[\\.0]*\\'\\%\\*\\%", "", l)
   # return this as an expression
   parse(text=l)
 }

结合一下，另外使用scale_x_reverse函数使x轴从大到小，并且使用breaks和labels指定要显示的数值和对应的标签

## 绘图
 library(ggpubr)
 library(ggthemes)
 ggscatter(draw.data, 
           x = "p_value", y = "fold",
           color = "group") + 
   theme_base()+
   scale_x_reverse(breaks = c(1,0.1,0.01,0.001,0.0001,0.00001,0.000001,0.0000001),
                   labels=fancy_scientific)

10.2 加y轴拉伸

然后我发现目标图像的y轴比例是调整过的于是坐标轴拉伸教程：《R画图y轴范围太大时，如何局部压缩坐标轴？》R画图y轴范围太大时，如何局部压缩坐标轴？- 知乎 (zhihu.com)

文章里作者给了个函数

 ###拉伸缩小坐标的函数
 library(scales)
 squash_axis <- function(from, to, factor) { 
   # Args:
   #   from: left end of the axis
   #   to: right end of the axis
   #   factor: the compression factor of the range [from, to]
   
   trans <- function(x) {    
     # get indices for the relevant regions
     isq <- x > from & x < to
     ito <- x >= to
     
     # apply transformation
     x[isq] <- from + (x[isq] - from)/factor
     x[ito] <- from + (to - from)/factor + (x[ito] - to)
     
     return(x)
   }
   
   inv <- function(x) {
     # get indices for the relevant regions
     isq <- x > from & x < from + (to - from)/factor
     ito <- x >= from + (to - from)/factor
     
     # apply transformation
     x[isq] <- from + (x[isq] - from) * factor
     x[ito] <- to + (x[ito] - (from + (to - from)/factor))
     
     return(x)
   }
   
   # return the transformation
   return(trans_new("squash_axis", trans, inv))
 }

于是我对y轴0.05-1.5范围的坐标轴拉伸了20倍，并且顺带指定了scale_y_continuous函数中的breaks和labels参数绘图代码如下

 ggscatter(draw.data, 
           x = "p_value", y = "fold",
           color = "group") + 
   theme_base()+
   coord_trans(y = squash_axis(0.05, 1.5, 0.05))+
   scale_y_continuous(breaks = c(0.05,0.5,1,5,50),
                      labels = c(0.05,0.5,1,5,50))+
   scale_x_reverse(breaks = c(1,0.1,0.01,0.001,0.0001,0.00001,0.000001,0.0000001),
                   labels=fancy_scientific)

图像如下~，能看到开始以1为轴进行分布了。很明显这张图的x轴和作者的图还有较大的差距因为人家的x轴长这样，是均匀分布的我想到一种可能，就是作者自己先计算了log10然后再和横坐标的标记进行对应。虽然显示的是10^-1，但实际上对应的数值是经过计算之后的0.1。

10.3 计算log10，加一列

x轴可能需要的是经过log后的数据，只不过标记的数值用的是科学计数法，相当于加了个标签那就，调整X轴数据，取个log10，然后标签加成科学计数法给表达矩阵加一列

 draw.data$Pvalue_log10=log10(draw.data$p_value)
draw.data=draw.data[-(1:10),]
draw.data=draw.data[draw.data$Pvalue_log10 != "-Inf",]
#save(draw.data,file = "drawdata.Rdata")

用于绘图的表达矩阵长这样~看见表达矩阵里面有Inf值，测试了一下虽然加着也能画，但强迫症到最后的最后还是删掉了...

10.4 更换x轴数值，调整x、y轴显示范围

coord_trans函数的ylim、xlim参数

 ggscatter(draw.data, 
           x = "Pvalue_log10", y = "fold",
           color = "group") + 
   theme_base()+
   #coord_cartesian(ylim = c(0.05, 50))+
   coord_trans(y = squash_axis(0.05, 1.4, 0.01),x=squash_axis(0,3,1),
               ylim = c(0.05,50),xlim = c(0,-5))+
   scale_y_continuous(breaks = c(0.05,0.5,1,5,50),
                      labels = c(0.05,0.5,1,5,50))+
   scale_x_reverse(breaks = c(0,-1,-2,-3,-4,-5,-6),
                   labels=c(expression(10^-0),expression(10^-1),
                            expression(10^-2),expression(10^-3),
                            expression(10^-4),expression(10^-5),
                            expression(10^-5)))

这下X轴标签对了看到整体上面有一团点我觉得可能是因为excle的表格数值精度有限，所以计算出来的P值的log10值对应的也是非常密集。从10.3部分可以看到有一堆-0.3000000，所以我觉得是正常的。

10.5 调整Y轴，更换图像主题

 ggscatter(draw.data, 
           x = "Pvalue_log10", y = "fold",
           color = "group") + 
   geom_point(alpha=0.1, size=0.5, shape=2,
              aes(color=group)) +
   #scale_color_manual(values=c("blue","red"))+
   theme_classic()+
   #coord_cartesian(ylim = c(0.05, 50))+
   coord_trans(y = squash_axis(0.05, 2.5, 0.008),x=squash_axis(0,3,1),
               ylim = c(0.05,50),xlim = c(0,-5))+
   scale_y_continuous(breaks = c(0.05,0.5,1,5,50),
                      labels = c(0.05,0.5,1,5,50))+
   scale_x_reverse(breaks = c(0,-1,-2,-3,-4,-5,-6),
                   labels=c(expression(10^-0),expression(10^-1),
                            expression(10^-2),expression(10^-3),
                            expression(10^-4),expression(10^-5),
                            expression(10^-5)))

差不多，加个注释线

10.6 添加注释线

 ggscatter(draw.data, 
           x = "Pvalue_log10", y = "fold",
           color = "group") + 
   geom_point(alpha=0.1, size=0.5, shape=2,
              aes(color=group)) +
   #scale_color_manual(values=c("blue","red"))+
   theme_classic()+
   #coord_cartesian(ylim = c(0.05, 50))+
   coord_trans(y = squash_axis(0.05, 2, 0.01),x=squash_axis(0,3,1),
               ylim = c(0.05,50),xlim = c(0,-5))+
   scale_y_continuous(breaks = c(0.05,0.5,1,5,50),
                      labels = c(0.05,0.5,1,5,50))+
   scale_x_reverse(breaks = c(0,-1,-2,-3,-4,-5,-6),
                   labels=c(expression(10^-0),expression(10^-1),
                            expression(10^-2),expression(10^-3),
                            expression(10^-4),expression(10^-5),
                            expression(10^-5)))+
   geom_vline(xintercept=-1.5,lty=4,col="grey",linewidth=0.8)+
   geom_hline(yintercept = 1,lty=1,col="black",linewidth=0.4)  ##加横线

好的注释线也加好了继续观察图像发现作者x\y轴的是相交的，不像我这个还有空余

10.7 让x轴的最小值和y轴相交

教程：《ggplot2中我如何让y轴与x轴相交0？- 优文库》 http://www.uwenku.com/question/p-cmjyklfm-uk.html 设置expand=c(0,0) 调整x\y轴

 ggscatter(draw.data, 
           x = "Pvalue_log10", y = "fold",
           color = "group") + 
   geom_point(alpha=0.1, size=0.5, shape=2,
              aes(color=group)) +
   #scale_color_manual(values=c("blue","red"))+
   theme_classic()+
   #coord_cartesian(ylim = c(0.05, 50))+
   coord_trans(y = squash_axis(0.05, 2, 0.01),x=squash_axis(0,3,1),
               ylim = c(0.05,50),xlim = c(0,-5))+
   scale_y_continuous(breaks = c(0.05,0.5,1,5,50),
                      labels = c(0.05,0.5,1,5,50),expand=c(0,0))+
   scale_x_reverse(breaks = c(0,-1,-2,-3,-4,-5,-6),
                   labels=c(expression(10^-0),expression(10^-1),
                            expression(10^-2),expression(10^-3),
                            expression(10^-4),expression(10^-5),
                            expression(10^-5)),expand=c(0,0))+
   geom_vline(xintercept=-1.5,lty=4,col="grey",linewidth=0.8)+
   geom_hline(yintercept = 1,lty=1,col="black",linewidth=0.4)  ##加横线

到目前已经让x轴和y轴中间没有保留了~ 嗯~长的已经比较像了，稍微美化一下吧

10.8 修改边框、图注、颜色...美化

用到的参考资料《玩转数据可视化之R语言ggplot2：（七）对图形添加注释和标签（包含标题、坐标轴、参考线和高亮等注释方法）》 https://blog.csdn.net/weixin_45052363/article/details/124153241#74__446 找到了一个设置主题的代码

   theme(axis.ticks.y = element_blank(),
         axis.text.y = element_text(size = 15, colour = "black" ),
         axis.text.x = element_text(size = 15, colour = "black" ),
         axis.ticks=element_blank(),
         axis.title.x=element_blank(),
         axis.title.y=element_blank())

直接加入

 ggscatter(draw.data, 
           x = "Pvalue_log10", y = "fold",
           color = "group",ylab="Fold change(vs. PBS)",rug = F,
           shape = 20,size = 3) +
     scale_color_manual(values=c( "#ff4757","#546de5"))+
   theme(axis.ticks.y = element_blank(),
         axis.text.y = element_text(size = 15, colour = "black" ),
         axis.text.x = element_text(size = 15, colour = "black" ),
         axis.ticks=element_blank(),
         axis.title.x=element_blank(),
         axis.title.y=element_blank())+
   coord_trans(y = squash_axis(0.05, 2, 0.01),x=squash_axis(0,3,1),
               ylim = c(0.05,50),xlim = c(0,-4.1))+
   scale_y_continuous(breaks = c(0.05,0.5,1,5,50),
                      labels = c(0.05,0.5,1,5,50),expand=c(0,0))+
   scale_x_reverse(breaks = c(0,-1,-2,-3),
                   labels=c(expression(10^-0),expression(10^-1),                      expression(10^-2),expression(10^-3)),expand=c(0,0))+geom_vline(xintercept=-1.301029995663981,lty=4,col="grey",linewidth=1)+
geom_hline(yintercept = 1,lty=1,col="black",linewidth=0.4)

好的，是时候加个基因标注了

10.9 加基因标注-geom_text_repel报错处理

需要标注哪些基因我得告诉R 所以先构建了新的矩阵

 library(ggstatsplot)
 library(ggrepel)
 up.article=c( "Angpt1","Pdgfrb","Cdh5","Sell","Ccr7","Cd86")
 down.article=c( "Cdh5","Mcam","Angpt1","Sell","Vegfa")
 up.gene=draw.data[draw.data$fold >1,][draw.data[draw.data$fold >1,]$gene %in% up.article,]
 down.gene=draw.data[draw.data$fold < 1,][draw.data[draw.data$fold < 1,]$gene %in% down.article,]
 diff.gene=rbind(up.gene,down.gene)
 diff.gene=diff.gene[!is.na(diff.gene),]
 diff.gene=na.omit(diff.gene)
 rownames(diff.gene)=1:11

其实之前在火山图里面看到过标注基因的代码于是上网找教程R语言实战：使用ggplot2包绘制个性化火山图 - 知乎 (zhihu.com)其实找了好几个教程,大佬们给的模板都大差不差，就不太多展示了。模板如下：

geom_text_repel(data = filter(data, abs(logFC) > 1 & -log10(adj.P.Val) > 38),
                  max.overlaps = getOption("ggrepel.max.overlaps", default = 20),
                  aes(label = gene, 
                      color = change),
                  size = 2)

用的是geom_text_repel函数但...报错了...

Error in `geom_label_repel()`:
! Problem while converting geom to grob.
ℹ Error occurred in the 2nd layer.
Caused by error in `x[isq] <- from + (x[isq] - from) / factor`:
! NAs are not allowed in subscripted assignments
Run `rlang::last_trace()` to see where the error occurred.

网上找了一圈，没有进展去看geom_text_repel说明书，结合报错里面也有NA看到了这个参数里面有NA 于是就试了试，把xlim和ylim设置了一下

ggscatter(draw.data, 
           x = "Pvalue_log10", y = "fold",
           color = "group",ylab="Fold change(vs. PBS)",rug = F,
           shape = 20,size = 3) +
     #geom_point(alpha=0.4, size=3.5) +
     scale_color_manual(values=c( "#ff4757","#546de5"))+
   ##加横线
   geom_label_repel(data = diff.gene, aes(x = diff.gene$Pvalue_log10,
                                          y = diff.gene$fold,
                                          label = gene),
                    size = 3, box.padding = unit(0.4, "lines"),
                    point.padding = unit(0.8, "lines"),
                    segment.color = "black",
                    show.legend = FALSE,
                    na.rm = T,
                    ylim = c(0.05,50),xlim = c(3,4),
                    direction = "y") +
   #directlabels::geom_dl(aes(label = group), method = "smart.grid")+
   #scale_colour_discrete(guide="none")
   theme(axis.ticks.y = element_blank(),
         axis.text.y = element_text(size = 15, colour = "black" ),
         axis.text.x = element_text(size = 15, colour = "black" ),
         axis.ticks=element_blank(),
         axis.title.x=element_blank(),
         axis.title.y=element_blank())+
   coord_trans(y = squash_axis(0.05, 2, 0.01),x=squash_axis(0,3,1),
               ylim = c(0.05,50),xlim = c(0,-4.1))+
   scale_y_continuous(breaks = c(0.05,0.5,1,5,50),
                      labels = c(0.05,0.5,1,5,50),expand=c(0,0))+
   scale_x_reverse(breaks = c(0,-1,-2,-3),
                   labels=c(expression(10^-0),expression(10^-1),
                   expression(10^-2),expression(10^-3)),expand=c(0,0))+geom_vline(xintercept=-1.301029995663981,lty=4,col="grey",linewidth=1)+
   geom_hline(yintercept = 1,lty=1,col="black",linewidth=0.4)

？？x和y轴的名称不知道什么时候没有了，原来是theme这里覆盖了.. 修改代码

ggscatter(draw.data, 
           x = "Pvalue_log10", y = "fold",
           color = "group",ylab="Fold change(vs. PBS)",rug = F,
           shape = 20,size = 3) +
     #geom_point(alpha=0.4, size=3.5) +
     scale_color_manual(values=c( "#ff4757","#546de5"))+
   ##加横线
   geom_label_repel(data = diff.gene, aes(x = diff.gene$Pvalue_log10,
                                          y = diff.gene$fold,
                                          label = gene),
                    size = 3, box.padding = unit(0.4, "lines"),
                    point.padding = unit(0.8, "lines"),
                    segment.color = "black",
                    show.legend = FALSE,
                    na.rm = T,
                    ylim = c(0.05,50),xlim = c(3,4),
                    direction = "y") +
   #directlabels::geom_dl(aes(label = group), method = "smart.grid")+
   #scale_colour_discrete(guide="none")
   theme(axis.ticks.y = element_blank(),
         axis.text.y = element_text(size = 15, colour = "black" ),
         axis.text.x = element_text(size = 15, colour = "black" ),
         axis.ticks=element_blank())+
   coord_trans(y = squash_axis(0.05, 2, 0.01),x=squash_axis(0,3,1),
               ylim = c(0.05,50),xlim = c(0,-4.1))+
   scale_y_continuous(breaks = c(0.05,0.5,1,5,50),
                      labels = c(0.05,0.5,1,5,50),expand=c(0,0))+
   scale_x_reverse(breaks = c(0,-1,-2,-3),
                   labels=c(expression(10^-0),expression(10^-1),
                   expression(10^-2),expression(10^-3)),expand=c(0,0))+geom_vline(xintercept=-1.301029995663981,lty=4,col="grey",linewidth=1)+
   geom_hline(yintercept = 1,lty=1,col="black",linewidth=0.4)

但我发现我的刻度线也不见了，就上面这个家伙... 继续搜索教程~

10.10 修改坐标轴刻度

让我康康这样的刻度要怎么才能让它再度出现，上网搜，教程如下 https://blog.csdn.net/qq_42458954/article/details/112604443 《6.7 坐标轴：移除刻度标签、刻度线和主网格线（关于刻度的逻辑）》 https://zhuanlan.zhihu.com/p/111896783 找到个具体名称介绍的但搜到的资料显示，通过主题的修改，刻度标签和刻度线总是需要同时出现的.. 那么，作者是如何做到部分有刻度线但没有刻度标签的.. 修改的时候发现自己设置的主题是没有刻度线的，于是修改了主题难道...等等我有一个大胆的猜测在设置scale_y_continuous，scale_x_reverse两个函数的时候label的可以直接为空？试一下

 ggscatter(draw.data, 
           x = "Pvalue_log10", y = "fold",
           color = "group",ylab="Fold change(vs. PBS)",xlab = "P-value",rug = F,
           shape = 20,size = 3) +
     scale_color_manual(values=c( "#ff4757","#546de5"))+
   geom_label_repel(data = diff.gene, aes(x = diff.gene$Pvalue_log10,
                                          y = diff.gene$fold,
                                          label = gene),
                    size = 3, box.padding = unit(0.4, "lines"),
                    point.padding = unit(0.8, "lines"),
                    segment.color = "black",
                    show.legend = FALSE,
                    na.rm = T,
                    ylim = c(0.05,50),xlim = c(3,4),
                    direction = "y") +
   theme_classic()+
   theme(
         axis.text.y = element_text(size = 10, colour = "black" ),
         axis.text.x = element_text(size = 10, colour = "black" ))+
   coord_trans(y = squash_axis(0.05, 2, 0.01),x=squash_axis(0,3,1),
               ylim = c(0.05,50),xlim = c(0,-4.1))+
   scale_y_continuous(breaks = c(0.05,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,
                                 1,5,50),
                      labels = c(0.05,"","","","",0.5,"","",'','',
                                 1,5,50),expand=c(0,0))+
   scale_x_reverse(breaks = c(0,-0.1,-0.2,-0.3,-0.4,-0.5,-0.6,-0.7,-0.8,
                              -1,-2,-3),
                   labels=c(expression(10^-0),'','','','','','','','',
                            expression(10^-1),
                            expression(10^-2),expression(10^-3)),expand=c(0,0))+geom_vline(xintercept=-1.301029995663981,lty=4,col="grey",linewidth=1)+
   geom_hline(yintercept = 1,lty=1,col="black",linewidth=0.4)

好耶，刻度线这不就加上了嘛是时候删除右边的图例了..

10.11 删图例，加注释（分组\P值）

删除图例教程：

https://blog.csdn.net/LeaningR/article/details/114576555 legend.title=element_blank()

但是....没有发现不同的分组可以用不同颜色的字来表示。

感觉分组是作者另外加的注释

找到的教程：《ggplot中的注释图层annotate》

ggplot中的注释图层

annotate_zoujiahui_2018的博客-CSDN博客《R语言ggplot2包之注释》

R语言ggplot2包之注释_r语言 ggplot annotate parse_zx403413599的博客-CSDN博客

P值的注释是竖的，所以，搜到的教程~

修改注释字的角度

《如何在ggplot2中旋转图中的注释文本（附实例）》 https://juejin.cn/post/7117025583959113764

而且这个P一看就是斜体，所以还要知道怎么样设置字体

设置字体

《ggplot2|theme主题设置，详解绘图优化-“精雕细琢”》

ggplot2|theme主题设置，详解绘图优化-“精雕细琢” - 知乎 (zhihu.com)

分组的注释是两行的，我该如何表示换行？

于是搜索的教程：双""中间表示换行《 R中转义符》 https://www.douban.com/note/512515819/?_i=9842178-fjctlC

综合以上的信息我设置了三个annotate函数

ggscatter(draw.data, 
           x = "Pvalue_log10", y = "fold",
           color = "group",ylab="Fold change(vs. PBS)",xlab = "P-value",rug = F,
           shape = 20,size = 3) +
     scale_color_manual(values=c( "#ff4757","#546de5"))+
   geom_label_repel(data = diff.gene, aes(x = diff.gene$Pvalue_log10,
                                          y = diff.gene$fold,
                                          label = gene),
                    size = 3, box.padding = unit(0.4, "lines"),
                    point.padding = unit(0.8, "lines"),
                    segment.color = "black",
                    show.legend = FALSE,
                    na.rm = T,
                    ylim = c(0.05,50),xlim = c(3,4),
                    direction = "y") +
   theme_classic()+
   theme(axis.text.y = element_text(size = 10, colour = "black" ),
         axis.text.x = element_text(size = 10, colour = "black" ),
         #legend.title=element_blank(),
         legend.position = "none")+
   coord_trans(y = squash_axis(0.05, 2, 0.01),x=squash_axis(0,3,1),
               ylim = c(0.05,50),xlim = c(0,-6.1))+
   scale_y_continuous(breaks = c(0.05,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,
                                 1,5,50),
                      labels = c(0.05,"","","","",0.5,"","",'','',
                                 1,5,50),expand=c(0,0))+
   scale_x_reverse(breaks = c(0,-0.1,-0.2,-0.3,-0.4,-0.5,-0.6,-0.7,-0.8,
                              -1,-2,-3,-4,-5,-6),
                   labels=c(expression(10^-0),'','','','','','','','',
                            expression(10^-1),
                            expression(10^-2),
                            expression(10^-3),
                            expression(10^-4),
                            expression(10^-5),
                            expression(10^-6)),
                   expand=c(0,0))+geom_vline(xintercept=-1.301029995663981,lty=4,col="grey",linewidth=1)+
   geom_hline(yintercept = 1,lty=1,col="black",linewidth=0.4)+
   annotate('text',x=-5,y=40,label="STING \n activated",color="#ff4757")+
   annotate('text',x=-5,y=0.2,label="STING \n deficient",color="#546de5")+
annotate('text',x=-1,y=34,label="P=0.05",color="black",angle=90,fontface="italic")

得到的图如下：

这个时候跟大家再提一嘴原图，不然可能都忘了..很明显，原图是没有x轴的

10.12 去x轴，加线段

于是又开始搜教程，如何去掉x轴，然后怎么样才能给注释线加上标尺... 找到的教程5.4 添加注释：添加线段(segment) - 知乎 (zhihu.com)《ggplot2作图：隐去坐标轴标签（xlab、ylab）》ggplot2作图：隐去坐标轴标签（xlab、ylab） - 知乎 (zhihu.com)《# ggplot2 line types : How to change line types of a graph in R software?》线型 http://www.sthda.com/english/wiki/ggplot2-line-types-how-to-change-line-types-of-a-graph-in-r-software 综合以上教程，以下代码我一共做了2件事 1-我把theme函数里面所有关于x轴的参数全部设置为空 2-然后我把线段标注当成坐标刻度绘制在注释线上..

 ggscatter(draw.data, 
           x = "Pvalue_log10", y = "fold",
           color = "group",ylab="Fold change(vs. PBS)",xlab = "",rug = F,
           shape = 20,size = 3,show.legend.text = T,ggtheme = theme_void()) +
     scale_color_manual(values=c( "#ff4757","#546de5"))+
   ##加标签
   geom_label_repel(data = diff.gene, aes(x = diff.gene$Pvalue_log10,
                                          y = diff.gene$fold,
                                          label = gene),
                    size = 3, box.padding = unit(0.4, "lines"),
                    point.padding = unit(0.8, "lines"),
                    segment.color = "black",
                    show.legend = FALSE,
                    na.rm = T,
                    ylim = c(0.05,50),xlim = c(3,4),
                    direction = "y") +
   theme_classic()+
   theme(#axis.text.y = element_text(size = 10, colour = "black" ),
         #axis.text.x = element_text(size = 10, colour = "black" ),
         #legend.title=element_blank(),
         legend.position = "none",
         axis.ticks.x = element_blank(),
         axis.text.x=element_blank(),
         axis.line.x=element_blank()
         )+
   coord_trans(y = squash_axis(0.05, 2, 0.01),x=squash_axis(0,3,1),
               ylim = c(0.05,50),xlim = c(0,-6))+
   scale_y_continuous(breaks = c(0.05,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,
                                 1,5,50),
                      labels = c(0.05,"","","","",0.5,"","",'','',
                                 1,5,50),expand=c(0,0))+
   scale_x_reverse(#breaks = c(0,-0.1,-0.2,-0.3,-0.4,-0.5,-0.6,-0.7,-0.8,-1,-2,-3,-4,-5,-6),
                   # labels=c(expression(10^-0),'','','','','','','','',
                   #          expression(10^-1),
                   #          expression(10^-2),
                   #          expression(10^-3),
                   #          expression(10^-4),
                   #          expression(10^-5),
                   #          expression(10^-6)),
                   expand=c(0,0),
                   breaks = NULL)+geom_vline(xintercept=-1.301029995663981,lty=4,col="grey",linewidth=1)+
   geom_hline(yintercept = 1,lty=1,col="black",linewidth=0.4)+
   annotate('text',x=-4.3,y=40,label="STING \n activated",color="#ff4757")+
   annotate('text',x=-4.3,y=0.2,label="STING \n deficient",color="#546de5")+
   annotate('text',x=-1.2,y=34,label="P=0.05",color="black",angle=90,fontface="italic")+
   annotate('segment',x = -0.1, xend = -0.1, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -0.15, xend = -0.15, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -0.22, xend = -0.22, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -0.31, xend = -0.31, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -0.25, xend = -0.25, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -0.28, xend = -0.28, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('text',x=-0.2,y=0.94,label=expression(10^-0),color="black",fontface="bold")+
   annotate('text',x=-1.1,y=0.94,label=expression(10^-1),color="black",fontface="bold")+
   annotate('segment',x = -1, xend = -1, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -1.2, xend = -1.2, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('text',x=-2.1,y=0.94,label=expression(10^-2),color="black",fontface="bold")+
   annotate('segment',x = -2, xend = -2, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -2.2, xend = -2.2, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('text',x=-3.1,y=0.94,label=expression(10^-3),color="black",fontface="bold")+
   annotate('segment',x = -3, xend = -3, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -3.2, xend = -3.2, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('text',x=-4.1,y=0.94,label=expression(10^-4),color="black",fontface="bold")+
   annotate('segment',x = -4, xend = -4, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -4.2, xend = -4.2, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('text',x=-5.1,y=0.94,label=expression(10^-5),color="black",fontface="bold")+
   annotate('segment',x = -5, xend = -5, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -5.2, xend = -5.2, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('text',x=-5.85,y=0.94,label=expression(10^-6),color="black",fontface="bold")+
   annotate('segment',x = -6, xend = -6, y = 0.98, yend = 1,color="black",size=0.001)

终于..标上了再对照了一下作者的图，发现颜色是渐变的

10.13 加渐变色...

...看起来是渐变色，其实是4个颜色.. 于是就先先添加用于分组的列

 draw.data$color_4 = ifelse(draw.data$fold >= 1 & draw.data$p_value < 0.05,"goodup",
                             ifelse(draw.data$fold >= 1 & draw.data$p_value >= 0.05,"up",
                                    ifelse(draw.data$fold <= 1 & draw.data$p_value >= 0.05,"down",
                                           "gooddown")))
head(draw.data)
 # gene      fold p_value           group Pvalue_log10  color_4
 # 11   Klrd1 2.9291279   0.001 STING activated           -3   goodup
 # 12 Tnfsf11 2.2882951   0.001 STING activated           -3   goodup
 # 13    Gbp5 4.3578296   0.001 STING activated           -3   goodup
 # 14   Pdcd1 2.9417155   0.001 STING activated           -3   goodup
 # 15    Cd40 3.2617735   0.001 STING activated           -3   goodup
 # 16   Birc5 0.7692822   0.001 STING activated           -3 gooddown

修改分组列修改scale_color_manual函数

ggscatter(draw.data, 
           x = "Pvalue_log10", y = "fold",
           color = "color_4",ylab="Fold change(vs. PBS)",xlab = "",rug = F,
           shape = 20,size = 3,show.legend.text = T,ggtheme = theme_void()) +
     scale_color_manual(values=c( "#96a6ef","#546de5","#ff4757","#ffbdc2"))+
   ##加标签
   geom_label_repel(data = diff.gene, aes(x = diff.gene$Pvalue_log10,
                                          y = diff.gene$fold,
                                          label = gene),
                    size = 3, box.padding = unit(0.4, "lines"),
                    point.padding = unit(0.8, "lines"),
                    segment.color = "black",
                    show.legend = FALSE,
                    na.rm = T,
                    ylim = c(0.05,50),xlim = c(3,4),
                    direction = "y") +
   theme_classic()+
   theme(#axis.text.y = element_text(size = 10, colour = "black" ),
         #axis.text.x = element_text(size = 10, colour = "black" ),
         #legend.title=element_blank(),
         legend.position = "none",
         axis.ticks.x = element_blank(),
         axis.text.x=element_blank(),
         axis.line.x=element_blank()
         )+
   coord_trans(y = squash_axis(0.05, 2, 0.01),x=squash_axis(0,3,1),
               ylim = c(0.05,50),xlim = c(0,-6))+
   scale_y_continuous(breaks = c(0.05,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,
                                 1,5,50),
                      labels = c(0.05,"","","","",0.5,"","",'','',
                                 1,5,50),expand=c(0,0))+
   scale_x_reverse(#breaks = c(0,-0.1,-0.2,-0.3,-0.4,-0.5,-0.6,-0.7,-0.8,-1,-2,-3,-4,-5,-6),
                   # labels=c(expression(10^-0),'','','','','','','','',
                   #          expression(10^-1),
                   #          expression(10^-2),
                   #          expression(10^-3),
                   #          expression(10^-4),
                   #          expression(10^-5),
                   #          expression(10^-6)),
                   expand=c(0,0),
                   breaks = NULL)+
   geom_vline(xintercept=-1.301029995663981,lty=4,col="grey",linewidth=1)+
   geom_hline(yintercept = 1,lty=1,col="black",linewidth=0.4)+
   annotate('text',x=-4.3,y=40,label="STING \n activated",color="#ff4757")+
   annotate('text',x=-4.3,y=0.2,label="STING \n deficient",color="#546de5")+
   annotate('text',x=-1.2,y=34,label="P=0.05",color="black",angle=90,fontface="italic")+
   annotate('text',x=-5.5,y=1.099,label="P-value",color="black",fontface="italic")+
   annotate('segment',x = -0.1, xend = -0.1, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -0.15, xend = -0.15, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -0.22, xend = -0.22, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -0.31, xend = -0.31, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -0.25, xend = -0.25, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -0.28, xend = -0.28, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('text',x=-0.2,y=0.94,label=expression(10^-0),color="black",fontface="bold")+
   annotate('text',x=-1.1,y=0.94,label=expression(10^-1),color="black",fontface="bold")+
   annotate('segment',x = -1, xend = -1, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -1.2, xend = -1.2, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('text',x=-2.1,y=0.94,label=expression(10^-2),color="black",fontface="bold")+
   annotate('segment',x = -2, xend = -2, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -2.2, xend = -2.2, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('text',x=-3.1,y=0.94,label=expression(10^-3),color="black",fontface="bold")+
   annotate('segment',x = -3, xend = -3, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -3.2, xend = -3.2, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('text',x=-4.1,y=0.94,label=expression(10^-4),color="black",fontface="bold")+
   annotate('segment',x = -4, xend = -4, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -4.2, xend = -4.2, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('text',x=-5.1,y=0.94,label=expression(10^-5),color="black",fontface="bold")+
   annotate('segment',x = -5, xend = -5, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('segment',x = -5.2, xend = -5.2, y = 0.98, yend = 1,color="black",size=0.001)+
   annotate('text',x=-5.85,y=0.94,label=expression(10^-6),color="black",fontface="bold")+
   annotate('segment',x = -6, xend = -6, y = 0.98, yend = 1,color="black",size=0.001)