RNA-seq学习：No.11 oligo包读取Array芯片原始数据(CEL.gz))

• oligo包官方介绍：https://bioconductor.org/packages/release/bioc/html/oligo.html
• oligo包简单教程：https://kasperdanielhansen.github.io/genbioconductor/html/oligo.html

• 示例数据：GSE159676

  
  

step1：下载Array芯片原始数据(CEL.gz))

• https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE159676
  以LTH与NASH组样本为例：

list.files("GSE159676_RAW/")
# [1] "GSM4837490_2010-03-26_LTH_1_HuGene-1_0-st-v1_.CEL.gz" 
# [2] "GSM4837491_2010-03-26_LTH_2_HuGene-1_0-st-v1_.CEL.gz" 
# [3] "GSM4837492_2010-04-01_LTH_3_HuGene-1_0-st-v1_.CEL.gz" 
# [4] "GSM4837493_2010-04-01_LTH_4_HuGene-1_0-st-v1_.CEL.gz" 
# [5] "GSM4837494_2010-04-01_LTH_5_HuGene-1_0-st-v1_.CEL.gz" 
# [6] "GSM4837495_2010-04-01_LTH_6_HuGene-1_0-st-v1_.CEL.gz" 
# [7] "GSM4837496_2010-03-26_NASH_1_HuGene-1_0-st-v1_.CEL.gz"
# [8] "GSM4837497_2010-04-01_NASH_2_HuGene-1_0-st-v1_.CEL.gz"
# [9] "GSM4837498_2010-04-01_NASH_3_HuGene-1_0-st-v1_.CEL.gz"
# [10] "GSM4837499_2010-04-01_NASH_4_HuGene-1_0-st-v1_.CEL.gz"
# [11] "GSM4837500_2010-04-01_NASH_5_HuGene-1_0-st-v1_.CEL.gz"
# [12] "GSM4837501_2010-04-15_NASH_6_HuGene-1_0-st-v1_.CEL.gz"
# [13] "GSM4837502_2010-04-15_NASH_7_HuGene-1_0-st-v1_.CEL.gz"

step2：加载R包，初步读取表达数据

library(oligo)
celfiles <- list.files("GSE159676_RAW", full = TRUE)
rawData <- read.celfiles(celfiles)
exprs(rawData)[1:4,1:3]
# GSM4837490_2010-03-26_LTH_1_HuGene-1_0-st-v1_.CEL.gz
# 1                                                 2530
# 2                                                   40
# 3                                                 2435
# 4                                                   55
# GSM4837491_2010-03-26_LTH_2_HuGene-1_0-st-v1_.CEL.gz
# 1                                                 2576
# 2                                                   42
# 3                                                 2612
# 4                                                   31
# GSM4837492_2010-04-01_LTH_3_HuGene-1_0-st-v1_.CEL.gz
# 1                                                 2302
# 2                                                   44
# 3                                                 2333
# 4                                                   48

summary(exprs(rawData)[, 1:3])
# GSM4837490_2010-03-26_LTH_1_HuGene-1_0-st-v1_.CEL.gz
# Min.   :   20.0                                     
# 1st Qu.:   35.0                                     
# Median :   67.0                                     
# Mean   :  254.9                                     
# 3rd Qu.:  181.0                                     
# Max.   :18087.0                                     
# GSM4837491_2010-03-26_LTH_2_HuGene-1_0-st-v1_.CEL.gz
# Min.   :   19.0                                     
# 1st Qu.:   32.0                                     
# Median :   52.0                                     
# Mean   :  175.4                                     
# 3rd Qu.:  119.0                                     
# Max.   :13711.0                                     
# GSM4837492_2010-04-01_LTH_3_HuGene-1_0-st-v1_.CEL.gz
# Min.   :   20.0                                     
# 1st Qu.:   35.0                                     
# Median :   64.0                                     
# Mean   :  243.1                                     
# 3rd Qu.:  167.0                                     
# Max.   :14906.0  

step3：修改组别名信息

filename = sampleNames(rawData)
filename_split = stringr::str_split(filename, "_", simplify = TRUE)
sampleNames(rawData) = filename_split[,1]
pData(rawData)$GSM = filename_split[,1]
pData(rawData)$Group = filename_split[,3]
head(pData(rawData))
#            index        GSM Group
# GSM4837490     1 GSM4837490   LTH
# GSM4837491     2 GSM4837491   LTH
# GSM4837492     3 GSM4837492   LTH
# GSM4837493     4 GSM4837493   LTH
# GSM4837494     5 GSM4837494   LTH
# GSM4837495     6 GSM4837495   LTH

exprs(rawData)[1:4,1:3]
#   GSM4837490 GSM4837491 GSM4837492
# 1       2530       2576       2302
# 2         40         42         44
# 3       2435       2612       2333
# 4         55         31         48

step4：表达数据标准化

normData <- rma(rawData)
# Background correcting
# Normalizing
# Calculating Expression

exprs(normData)[1:4,1:3]
#         GSM4837490 GSM4837491 GSM4837492
# 7892501   2.829734   1.202127   2.415802
# 7892502   3.680496   3.178658   3.480709
# 7892503   2.693415   2.391527   2.351842
# 7892504   7.416071   7.063614   7.214720

class(normData)
# [1] "ExpressionSet"
# attr(,"package")
# [1] "Biobase"