如何使你的数据更为整洁呢？建议尝试下tidyr包。
Introducing tidyr：tidyr is new package that makes it easy to “tidy” your data.
安装失败，尝试安装“tidyverse”包，加载失败报错，报错如下：
─ Conflicts ─────── tidyverse_conflicts() ─
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
尝试：library(dplyr)，正常运行
创建数据集：
frame1<-data.frame(geneid=paste("gene",1:4,sep=""),Sample1=c(1,3,6,9),Sample2=c(2,5,0.8,11),Sample3=(c(40,70,80,35)))
使用gather函数：
frame2<-gather(frame1,"Sampleid","expression",Sample1,Sample2,Sample3)
#按照geneid排序
frame3<-arrange(frame2,geneid)
#空值操作用表
frame4<-data.frame(geneid = paste("gene",1:3,sep=""),annotion=paste( c("aaa","bbb","ccc"),"relate") )
left_join(frame3,frame4,by="geneid")
创建新的数据集，如图所示，代码贴在下边。
messy <- data.frame( name = c("Wilbur", "Petunia", "Gregory"), a = c(67, 80, 64), b = c(56, 90, 50))
messy %>% gather(drug, heartrate, a:b)
set.seed(10)
messy <- data.frame( id = 1:4, trt = sample(rep(c('control', 'treatment'), each = 2)), work.T1 = runif(4), home.T1 = runif(4), work.T2 = runif(4), home.T2 = runif(4))
tidier <- messy %>%
gather(key, time, -id, -trt)
tidier %>% head(8)
tidy <- tidier %>%
separate(key, into = c("location", "time1"), sep = "\\.")