输入数据
Rscript #读取数据 a<-read.table("../data/All.lib.list.modified.ref.hits.data1",header = T) ##对分类进行排序 a$ref=factor(a$ref,levels = c("ref1","ref2","ref3","ref4","ref5","ref6","ref7","ref8","ref9","ref10")) ##建立每个分面的R<sup>2</sup>值和p-value值 lm_labels<-function(dat){ tmp = cor.test(dat$Rnum,dat$hits,method="pearson") r<-sprintf("italic(R^2)==%.3f", tmp$estimate) p<-sprintf("italic(p-vaule)==%.3f",tmp$p.value) data.frame(r=r,p=p,stringsAsFators=FALSE) } library(plyr) labels<-ddply(a,"ref",lm_labels) ##使用ggplot画图 library(ggplot2) p<-ggplot(data=a,aes(x=Rnum/1000000,y=hits,color=ref))+ geom_point()+stat_smooth()+ theme(axis.text.x=element_text(size=8,vjust=1,hjust=1,angle=45))+ facet_wrap(.~ref,nrow=2)+ scale_x_continuous(breaks=seq(100,1500, 100))+ geom_text(x=300,y=500,aes(label=r),data=labels,parse=TRUE)+ geom_text(x=300,y=450,aes(label=p),data=labels,parse=TRUE) p 输出的结果转载于:https://www.cnblogs.com/RyannBio/p/10717777.html
