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RNA-seq学习:No.11 oligo包读取Array芯片原

RNA-seq学习:No.11 oligo包读取Array芯片原

作者: 小贝学生信 | 来源:发表于2021-12-30 21:14 被阅读0次

    step1:下载Array芯片原始数据(CEL.gz))

    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"
    

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