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  • skewed MAplot - DESeq

    Hi,

    As seen below my MAplots for RNAseq from DESeq are a bit skewed;
    To me 2 and 3 are acceptable while no. 1 show clear slope suggesting that there is more upregulation of genes with lower expression and etc.
    is this a normalization artifact?

    I would appreciate for any suggestion, I tried to estimate dispersions in different ways, also different combination between replicates, still the same...

    1.pdf


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    Last edited by ekimmike; 10-03-2012, 02:10 AM. Reason: pic upload

  • #2
    If only look at the MA plot, it is obvious that the condition 1 are skewed , suggesting upregulation.

    RNA-seq is better than microarray in low-abundance quantification. So I think the result in condition is not due to noise or detection limit. But different library construction could lead to protocol-dependent biases due to GC content and transcript length as well as stereotypic heterogeneity in coverage across transcripts correlated with position relative to RNA termini and priming sequence bias.[1] Maybe you should take a look at these biases.



    [1]Synthetic spike-in standards for RNA-seq experiments

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    • #3
      could this be a problem of mapping instead?

      Originally posted by Luyi Tian View Post
      If only look at the MA plot, it is obvious that the condition 1 are skewed , suggesting upregulation.
      I could send some more plots for diagnostics

      Originally posted by Luyi Tian View Post
      different library construction could lead to protocol-dependent biases due to GC content and transcript length as well as stereotypic heterogeneity in coverage across transcripts correlated with position relative to RNA termini and priming sequence bias.
      I tried to separate replicates and calculated DE for each case; sample which is more GC biased looks very similar


      Originally posted by Luyi Tian View Post
      Synthetic spike-in standards for RNA-seq experiments
      Actually, the size factors assigned based on 50 spike-ins are much worse than those calculated from DESeq based on library size

      Comment


      • #4
        I don't know.
        But personally speaking, I think bias caused by protocol or data processing method won't cause such obvious difference in two samples.

        Comment


        • #5
          I have the same problem, though my plots look much more skewed than that. If it's not library construction, then what could it be? Can there be a biological reason? My groups are very different from each other. I'm very interested in hearing your thoughts and advice.

          Comment


          • #6
            ekimmike, did you ever find out why you plot looked like that?

            Comment

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