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  • DESeq can not detect significant DE genes.

    Dear all,
    I recently used DEseq to call DE genes and I have successfully run it for several dataset. However for the following dataset, I could not get any 'significant' DE gene with Padj < 0.05. Though, the within group variation between replicates are small and from the correlation between samples you can tell that CTR and Treated are obviously different. So my question is how could this happened? I have tried to figure out the problem but with no success.

    Here is my R command for the analysis:
    input file are attached behind. (ExperimentDesign.txt and RawCountTable.txt)
    =============================
    countTable.TBI.all = read.table("RawReadCount.txt",header=TRUE, row.names=1)
    designTable.TBI.all = read.table("ExperimentDesign.txt",header=TRUE, row.names=1)
    samples.CTR.vs.Treat = designTable.TBI.all$Condition == "CTR" | designTable.TBI.all$Condition =="Treat"
    countTable.CTR.vs.Treat = countTable.TBI.all[ , samples.CTR.vs.Treat]
    conditions.CTR.vs.Treat = designTable.TBI.all$Condition[samples.CTR.vs.Treat]
    conditions.CTR.vs.Treat = factor(conditions.CTR.vs.Treat)
    library(DESeq)
    CTR.vs.Treat.cds = newCountDataSet(countTable.CTR.vs.Treat, conditions.CTR.vs.Treat)
    CTR.vs.Treat.cds = estimateSizeFactors(CTR.vs.Treat.cds)
    CTR.vs.Treat.cds = estimateDispersions(CTR.vs.Treat.cds)
    CTR.vs.Treat.res = nbinomTest(CTR.vs.Treat.cds, "CTR", "Treat")
    ===================================================
    Attached Files

  • #2
    You just reversed the order of the treatment and control conditions.
    In your counts file, it's Treat1, Treat2, Treat3, CTR1, CTR2,
    In your conditions vector, it's CTR, CTR, Treat, Treat, Treat.
    It's actually reassuring that DESeq does not find any significant differences in gene expression with this input.

    > conditions.CTR.vs.Treat
    [1] CTR CTR Treat Treat Treat
    Levels: CTR Treat
    > head(countTable.CTR.vs.Treat)
    Treat1 Treat2 Treat3 CTR1 CTR2
    Mbp 255219 261306 295123 365033 415838
    Apoe 255618 333022 275713 31494 33771
    Gfap 135100 143838 143669 57978 62635
    Plp1 83787 92153 100662 165798 207643
    Fth1 97740 108155 113955 122369 117290
    Sparcl1 44654 43945 53549 72772 90997
    Last edited by blancha; 05-02-2014, 07:30 PM.

    Comment


    • #3
      Thank you very much blancha~
      Works like a charm.

      Comment

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