密码子偏好性绘图

将多个基因的cds用下面的网址获得结果
https://galaxy.pasteur.fr/?tool_id=toolshed.pasteur.fr%2Frepos%2Fkhillion%2Fcodonw%2Fcodonw%2F1.4.4&version=1.4.4&__identifer=zwhtdsoycw9
##选择Calculate Effective Number of Codons和Calculate GC of silent 3rd codon posit

结果如图，一共三列

image.png

修改为以下格式

image.png

这个结果用ggplot绘制保存为文件code.txt

ENC<-function(x){
  return(2 + x + 29/(x^2+(1-x)^2))
}
x <- seq(0,1,by=0.005)
y <- ENC(x)
df1<-data.frame(A=x,B=y)
library(ggplot2)
df <- read_delim("/your-path/code.txt", 
                     "\t", escape_double = FALSE, trim_ws = TRUE)
##只用前两列绘图
ggplot(df1,aes(x=A,y=B))+geom_line(size=1)+
  geom_point(data=df,aes(x=GC3s,y=ENC))+xlim(0,1)+
  ylim(0,70)+labs(x="GC3s",y="ENC")+theme_bw()

###到这一步有人遇到报错Error: `mapping` must be created by `aes()，具体是什么原因我不知道，对应着把geom_point(df,)改成geom_point(data=df)就不会有这个报错了。

image.png

##将第三列映射为颜色
ggplot(df1,aes(x=A,y=B))+geom_line(size=1)+
  geom_point(data=df,aes(x=GC3s,y=ENC,color=gene))+xlim(0,1)+
  ylim(0,70)+labs(x="GC3s",y="ENC")+theme_classic()+
  theme(legend.position="none")

image.png

添加标签

ggplot(df1,aes(x=A,y=B))+geom_line(size=1)+
  geom_point(data=df,aes(x=GC3s,y=ENC,color=gene))+xlim(0,1)+
  ylim(0,70)+labs(x="GC3s",y="ENC")+theme_classic()+
  geom_text(data=df,aes(x=GC3s,y=ENC,color=gene,label=gene))
  theme(legend.position="none")

image.png

存在重叠看不起
这里使用ggrepel包中的geom_text_repel函数，只需要将geom_text换成geom_text_repel即可。

library(ggrepel)
ggplot(df1,aes(x=A,y=B))+geom_line(size=1)+
  geom_point(data=df,aes(x=GC3s,y=ENC,color=gene))+xlim(0,1)+
  ylim(0,70)+labs(x="GC3s",y="ENC")+theme_classic()+
  geom_text_repel(data=df,aes(x=GC3s,y=ENC,color=gene,label=gene))
  theme(legend.position="none")

image.png

###绘制GC3s图
ENC<-function(x){
  return(2 + x + 29/(x^2+(1-x)^2))
}
x <- seq(0,1,by=0.005)
y <- ENC(x)
df1<-data.frame(A=x,B=y)
library(ggplot2)
df <- read_delim("~/yt/20230106_baimaike/0105_YC_hifi/mito_assemble_script/0314_comparate-mito/6-code/txt", 
                     "\t", escape_double = FALSE, trim_ws = TRUE)
ggplot(df1,aes(x=A,y=B))+geom_line(size=1)+
  geom_point(data=df,aes(x=GC3s,y=ENC))+xlim(0,1)+
  ylim(0,70)+labs(x="GC3s",y="ENC")+theme_bw()


ggplot(df1,aes(x=A,y=B))+geom_line(size=1)+
  geom_point(data=df,aes(x=GC3s,y=ENC,color=gene))+xlim(0,1)+
  ylim(0,70)+labs(x="GC3s",y="ENC")+theme_classic()+
  geom_text(data=df,aes(x=GC3s,y=ENC,color=gene,label=gene))
  theme(legend.position="none")


ggplot(df1,aes(x=A,y=B))+geom_line(size=1)+
  geom_point(data=df,aes(x=GC3s,y=ENC,color=gene))+xlim(0,1)+
  ylim(0,70)+labs(x="GC3s",y="ENC")+theme_classic()+
  geom_text_repel(data=df,aes(x=GC3s,y=ENC,color=gene,label=gene))
  theme(legend.position="none")

ggplot(df1,aes(x=A,y=B))+geom_line(size=1)+
  geom_point(data=df,aes(x=GC3s,y=ENC,color=gene))+xlim(0,1)+
  ylim(0,70)+labs(x="GC3s",y="ENC")+theme_classic()+
  geom_text_repel(data=df,aes(x=GC3s,y=ENC,color=gene,label=gene),fontface="bold", color="black")
  theme(legend.position="none")

参考https://www.jianshu.com/p/acb2736bccc2