一、实验分组

  1. rm(list = ls())  
  2. load(file = "step1output.Rdata")
  3. library(stringr)
  4. library(tinyarray)

1. 有现成的可以用来分组的列

Group = pd$`disease state:ch1`

2. 自己生成

Group = c(rep("RA",times=13),
          rep("control",times=9))
Group = rep(c("RA","control"),times = c(13,9))

3. 匹配关键词，自行分类

Group=ifelse(str_detect(pd$source_name_ch1,"control"),
             "control",
             "RA")

4. 设置参考水平，指定levels，对照组在前，处理组在后

Group = factor(Group,
               levels = c("control","RA"))
Group

二、探针注释的获取

1. 捷径

find_anno(gpl_number)
ids <- AnnoProbe::idmap('GPL570')

2. Bioconductor的注释R包(最常用)

http://www.bio-info-trainee.com/1399.html

gpl_number 
if(!require(hgu133plus2.db))BiocManager::install("hgu133plus2.db")
library(hgu133plus2.db)
ls("package:hgu133plus2.db")
ids <- toTable(hgu133plus2SYMBOL)
head(ids)

3. 读取GPL平台的soft文件，按列取子集

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL570
注：soft文件列名不统一，活学活用，有的表格里没有symbol列，也有的GPL平台没有提供注释

## 网页下载注释文件，用的是.soft的文件，AnnotGPL = F
GPL_data <- getGEO(filename = "GPL10295_family.soft.gz", AnnotGPL = F)
GPL_data_1 <- Table(GPL_data)

ids <- GPL_data_1 %>% 
  dplyr::select(ID, Symbol)

## 生信技能树代码
if(F){
  a = getGEO(gpl_number,destdir = ".")
  b = a@dataTable@table
  colnames(b)
  ids2 = b[,c("ID","Gene Symbol")]
  colnames(ids2) = c("probe_id","symbol")
  ids2 = ids2[ids2$symbol!="" & !str_detect(ids2$symbol,"///"),]
}

4. 官网下载注释文件并读取

http://www.affymetrix.com/support/technical/byproduct.affx?product=hg-u133-plus

5. 自主注释

https://mp.weixin.qq.com/s/mrtjpN8yDKUdCSvSUuUwcA

三、保存数据

save(exp,Group,ids,gse_number,file = "step2output.Rdata")