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  • what statistics and tool to use?

    Dear all,
    Since I'm not so experienced in statistics most of the time I used deseq.
    I have 2 samples with 2 repetitions, and I want to see which are most changed and their p-values.
    The problem is in that particular case I do not have simple read counts, but already normalized and calculated by my own way values for a spesific task e.g.
    c-control
    s-treated
    name c1 s1 c2 s2
    gene1 0.03 0.1 0.01 0.6
    what statistics and what tool I can use and it is most relevant in that case?

    Thanks!!!!
    ------------
    SMART - bioinfo.uni-plovdiv.bg

  • #2
    You can try sam method, or moderated t-test

    Comment


    • #3
      Thanks,
      do you know what sotfware tool to use? since I'm not good in statistics for this moderated t-test?
      ------------
      SMART - bioinfo.uni-plovdiv.bg

      Comment


      • #4
        Do you know "R"?

        It has many tools to use.

        Comment


        • #5
          Poorly since I was using only deseq...

          But if there is no other way I will try to look for this, and try to find what R module can do this for me
          ------------
          SMART - bioinfo.uni-plovdiv.bg

          Comment


          • #6
            It's very simple, much more than deseq.

            you can use "sam" or "dchip" module.

            It depends on the distribution of your data. If it's normal distribution, the simplest method is t-test.

            Comment


            • #7
              Sorry for the stupid question but what it is mean by "normal distribution"
              ------------
              SMART - bioinfo.uni-plovdiv.bg

              Comment


              • #8
                see wiki:
                http://en.wikipedia.org/wiki/Normal_distribution.

                for simple, you can plot your data to see if it is symmetric and bell-shaped.

                but I doult it, most data didn't obey it. But it's good to see the distribution of your data at first.

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                • #9
                  Thanks a lot!
                  ------------
                  SMART - bioinfo.uni-plovdiv.bg

                  Comment


                  • #10
                    If your data are HTS reads, they don't follow a normal distribution. You've to use a non-parametric test like the Wilcoxon Test or the Kruskal-Wallis Test.

                    Comment


                    • #11
                      My data are not pure read counts, but rather a value that came from read counts normalized by the total library reads and how muuch times a read maps to a genome.
                      ------------
                      SMART - bioinfo.uni-plovdiv.bg

                      Comment


                      • #12
                        Originally posted by vebaev View Post
                        My data are not pure read counts, but rather a value that came from read counts normalized by the total library reads and how muuch times a read maps to a genome.
                        So you should use raw reads with DESeq or edgeR. It seems the best solution to your problem.

                        Comment


                        • #13
                          Yes but I wanted to take in consideration of how much a seq maps to a genome and deseq is not taking this into account?
                          If I have seq with read counts 10 that maps in 2 location perfectly, and I want to see if location 1 is changes in samples, it does not mean that all 10 reads are coming from location 1, isn,t it?

                          Or I'm somwhere wrong in my logic

                          Anyway, I will run this with deseq to see the result!
                          ------------
                          SMART - bioinfo.uni-plovdiv.bg

                          Comment


                          • #14
                            NicoBxl,

                            I have tun on my 4 samples (2 controles and 2 treatment) deseq with binomial test and I got list.

                            What about these genes that are 0 reads in one group and non-zero in the other group? I got =+Inf ot =-Inf? Should I took tham or discard them from the most diff.altered table?

                            Thanks
                            ------------
                            SMART - bioinfo.uni-plovdiv.bg

                            Comment


                            • #15
                              Originally posted by vebaev View Post
                              NicoBxl,

                              I have tun on my 4 samples (2 controles and 2 treatment) deseq with binomial test and I got list.

                              What about these genes that are 0 reads in one group and non-zero in the other group? I got =+Inf ot =-Inf? Should I took tham or discard them from the most diff.altered table?

                              Thanks
                              That's a tough question. Maybe check the p-value. What's the read count for the "other" group ?
                              Last edited by NicoBxl; 08-18-2011, 11:30 PM.

                              Comment

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