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  • CummeRbund shows 95% NAs for gene lists

    Code:
    cuff_data = readCufflinks(dir=paste0(getwd(),"/../cuffdiff/"), 
                              gtfFile = paste0(getwd(),"/../cuffmerge/merged.gtf"), 
                              genome="hg19", rebuild=F)
    
    #get significant IDs
    diffGeneIDs = getSig(cuff_data, level="genes", alpha=0.05)
    
    diffGenes = getGenes(cuff_data, diffGeneIDs)
    
    featureNames(diffGenes)[1:40,]
    tracking_id gene_short_name
    1 XLOC_000265 CROCC
    2 XLOC_000328 ALPL
    3 XLOC_000443 SYTL1
    4 XLOC_000679 ARTN
    5 XLOC_000938 RNU6-387P
    6 XLOC_001003 FAM73A,RNA5SP21
    7 XLOC_001244 GSTM1,GSTM2
    8 XLOC_001530 ADAMTSL4,AL356356.1,MIR4257
    9 XLOC_001735 FCER1A
    10 XLOC_001988 AXDND1
    11 XLOC_002089 RGS1
    12 XLOC_002211 NFASC,RP11-494K3.2
    13 XLOC_002282 HHAT,KCNH1
    14 XLOC_002522 RYR2
    15 XLOC_002961 PLA2G2A
    16 XLOC_003294 SLC2A1
    17 XLOC_003772 MIR137HG
    18 XLOC_004252 ASH1L,ASH1L-IT1,MIR555
    19 XLOC_004467 RP1-117P20.3,SELE
    20 XLOC_004799 CR1L
    21 XLOC_004802 CD34
    22 XLOC_004843 <NA>
    23 XLOC_005255 <NA>
    24 XLOC_005256 <NA>
    25 XLOC_005257 <NA>
    26 XLOC_005263 <NA>
    27 XLOC_005264 <NA>
    28 XLOC_005265 <NA>
    29 XLOC_005273 <NA>
    30 XLOC_005276 <NA>
    31 XLOC_005277 <NA>
    32 XLOC_005288 <NA>
    33 XLOC_005291 <NA>
    34 XLOC_005292 <NA>
    35 XLOC_005293 <NA>
    36 XLOC_005294 <NA>
    37 XLOC_005322 <NA>
    38 XLOC_005331 <NA>
    39 XLOC_005332 <NA>
    40 XLOC_005333 <NA>
    41 XLOC_005336 <NA>

    Code:
    mean(is.na(as.vector(featureNames(diffGenes)[2])))
    [1] 0.9691279

    This is human data and I have used the same GTF / genome data throughout, so why are so few genes labeled? Only about 3% of the total 6284 differentially expressed genes have labels.
    I have followed the protocol in the nature paper (tophat -> cufflinks -> cuffmerge -> cuffdiff)

    Thanks
    Last edited by bjackson; 05-11-2015, 05:55 PM.

  • #2
    Still looking through this data set. I have 194 named differentially expressed genes. What is the 'normal' amount of differentially expressed genes that you would expect? I know it can vary a lot based on how different the conditions are, but is this in the range of possibility? A lot of the unnamed bits are small chunks or exons. Does this sound like it might be a true result instead of an error in annotation?

    Comment

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