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  • EdgeR_normalization question

    I have two samples with very different composition: one sample contains many genes expressed at very high levels, which are not present in the other sample.

    I tried the TMM method (EdgeR_TMM). The scaling factor is around 5. I am very new at this, so I am not sure whether it is still valid in this range. Helps are greatly appreciated!

  • #2
    Dear Xiansan

    I think the answer of whether this is "valid" depends on your subsequent question. What is the aim of the experiment?

    Best wishes
    Wolfgang
    Wolfgang Huber
    EMBL

    Comment


    • #3
      Dear Wolfgang,

      Thanks so much for your help. Our data set is a time series, the aim is to detect distinct expression profiles that may correlate with distinct developmental processes.

      Our first 5 samples have similar transcriptom composition (scaling factor = 1 to 2). The last 3 samples have different composition due to the activation of a storage program. TMM normalization indicated that reads in sample 8 should be multiplied by 5 (SF=5 between sample 1 and 8). I am more of a biologist, so I don't feel very comfortable deciding whether to use TMM to normalize samples with dramatically different compositions.

      Thanks very much!

      xiansan

      Comment


      • #4
        Dear Xiansan

        thanks. My approach here would be to find control genes, for which you know from other sources that they are not changing between the first 5 and the latter 3 samples; or, for which know by how much they are changing. And then determine the size factors based on these.

        On a more philosophical note, in my experience the usefulness of differential expression analysis tends to be inversely related to the number of genes that are truly differentially expressed.

        Best wishes
        Wolfgang
        Wolfgang Huber
        EMBL

        Comment


        • #5
          Dear Wolfgang,

          Thanks very much for your suggestions, as well as your thoughts on our case. I suppose that we need to be more stringent when selecting differentially expressed genes in this particular case.

          xiansan

          Comment


          • #6
            Hi Xiansan,

            I suggest you visualise your data with something like an MAplot and see if that normalization factor looks about right. If you can see that there are really a group of genes that are very highly expressed in just one sample (group) then you can get factors that high and I have seen it before.

            Cheers,
            Alicia

            Comment


            • #7
              Hi Alicia,

              Thanks for your comments. The MA plot did indicate that there are a number of genes expressed in one of the samples at very high levels. It is very reassuring to know that someone else had similar experiences. Thanks very much.

              xiansan

              Comment

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