方法1，下载包后解压，ubunt20.04
vim /etc/apt/sources.list
deb https://mirrors.ustc.edu.cn/ubuntu/ xenial main restricted universe multiverse
deb-src https://mirrors.ustc.edu.cn/ubuntu/ xenial main restricted universe multiverse
:wq! #把ubunt16的源加进去
sudo apt-get install gcc-4.8 g++-4.8
R #进入R，把包解压后载入
library(peer,lib.loc= "/home/fanbaitong/bin")
Peer的包链接：
链接：https://pan.baidu.com/s/1Rk5zRnJJgK1rCO7cpunc9A
提取码：kn4y
方法2
R CMD INSTALL R_peer_source_1.3.tgz 报错！
#运行peer，合并实验组和对照组基因表达量TPM，作为输入文件
library(peer,lib.loc= "/home/fanbaitong/bin")
input = read.table('/home/fanbaitong/bin/GTEX_Minority_ebvlp.log2.txt', header=T,sep = "\t")
input<-data.frame(input)
expr<-input[,2:ncol(input)] #删除列名，运行完再补充上
dim(expr)
model = PEER() #创建模型
PEER_setPhenoMean(model,as.matrix(expr))
dim(PEER_getPhenoMean(model))
PEER_setNk(model,30) #文献推荐factors数目为样本量的1/4
PEER_getNk(model)
PEER_setNmax_iterations(model,1000)
PEER_update(model) #Converged (var(residuals)) after 8 iterations
factors = PEER_getX(model)
dim(factors)
weights = PEER_getW(model)
dim(weights)
precision = PEER_getAlpha(model)
dim(precision)
options(digits=3) #保留三位小数
residuals = PEER_getResiduals(model)
dim(residuals)
setwd("/home/fanbaitong/bin/")
#plot(precision)
PEER_setAdd_mean(model, TRUE)
write.table(residuals,file="/home/fanbaitong/bin/GTEX_Minority_ebvlp.residual.txt",append=T,row.names=F)
得到残差后用python计算z-score
