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  • #31
    Hi Simon,

    I'm new to DE analysis. Just tried DESeq for my dataset. FYI, the dataset don't have replicate. When running libsizes

    Code:
    > libsizes <- c(C=6821199 , E=6037299)
    when I checked the size factor, it show

    Code:
    > sizeFactors (cds)
    C             E
    1             1
    Is the size factor for both sample '1' is normal. Is it due to working with no replicate dataset?

    Comment


    • #32
      Doing DE analysis without any replicate in any of the condition is a none sense. You can not have significant results without replicates.

      For your question :

      I tried with artificial data and it works well.

      A <- data.frame(x=c(1000,10,10,10,0),y=c(100,2,2,2,1))
      conds<-c("a","b")
      cds <- newCountDataSet(A,conds)
      cds <- estimateSizeFactors(cds)
      sizeFactors(cds)
      x y
      2.2360680 0.4472136

      Comment


      • #33
        Hi NicoBxl

        I've tried plying with the example dataset. I treated only two sample (T1b and T2) trying to mimic my dataset as there is no replicate. I still got the sizeFactors not to '1' (as shown below). So I believed non replicate dataset is not an issue here.

        Code:
        > sizeFactors(cds)
             T1b       T2
        0.604218 1.655032
        Yes, now understand that without any replicate, its hard to get concrete conclusion on DE analysis. That is our mistakes here. Any how we try to get as much as possible input from our dataset.

        Still not sure what is the prob, why my sizeFactor = 1 on both sample.

        Comment


        • #34
          Hi

          Originally posted by masterpiece View Post
          Code:
          > libsizes <- c(C=6821199 , E=6037299)
          The vignette is a bit badly worded here. Ignore the part about the 'libsizes', you do not need this, and the information is overwritten, once you call 'estimateLibrarySizes'.

          Have you done this and the got this here?

          Code:
          > sizeFactors (cds)
          C             E
          1             1
          Make a plot with
          Code:
          plot( counts(cds)[,1] + .01, counts(cds)[,2] + .01, log="xy" )
          to see how your data looks.If you are still confused, show us the plot.

          Simon

          Comment


          • #35
            Hi Simon,

            Thanks for the reply. Hope I got you right. Using my dataset I've follow exactly as instructed in the tutorial until I got

            Code:
            > sizeFactors (cds)
            C             E
            1             1
            If i do not need to run libsizes, can I normalize my sample? About the 'estimateLibrarySizes'. Do i need to run them? because i can't see it in the DESeq

            I've create the plot. Attached is the plot
            Attached Files

            Comment


            • #36
              Originally posted by masterpiece View Post
              If i do not need to run libsizes, can I normalize my sample? About the 'estimateLibrarySizes'. Do i need to run them? because i can't see it in the DESeq
              I don't quite get your last sentence, but anyway. Them minimal set of commands you always need are:

              Code:
              cds <- newCountDataSet( countsTable, conds )
              cds <- estimateSizeFactors( cds )
              cds <- estimateVarianceFunctions( cds )
              res <- nbinomTest( cds, "T", "N")
              I've create the plot. Attached is the plot
              You could have maybe made it a little larger... Nevertheless, with quite some squinting, it seems to me that your data really scatters quite exactly around the x=y diagonal, i.e., it might be close to equal sequencing depth. If so, 1 and 1 as size factors should be fine.

              Simon

              Comment


              • #37
                Hi Simon,

                About the attachment, yup, tried to attach larger plot, but the maximum size attachment allowed is only 680x280. So the plot size has to be reduced. Sorry about that.

                Great. At least now I have some confident to work with the data. Thanks a lot for your explanation.

                Comment


                • #38
                  Hi masterpiece

                  I've got another report from somebody who got exactly 1 as size factors, and so had a closer look. The problem is that the size factor estimation tends to round values when you have many genes with only very few counts. So, I've just improved the method slightly and the newest version of DESeq, version 1.3.3, now offers a new optional argument to 'estimateSizeFactors'.

                  So, please try again, and now call estimateSizeFactors as follows:

                  Code:
                  library( genefilter )
                  cds <- estimateSizeFactors( cds, locfunc=shorth )
                  See help page to 'estimateSizeFactorsForMatrix' for details.

                  Version 1.3.3 is available via SVN now, and for download in a day or so.

                  Simon

                  Comment


                  • #39
                    Hi Simon,

                    It does make sense. Our data is from DGE sample and we dont do any count filtering on the data. I can say most of the sequence have very few count. I'll try redo the analysis.

                    Thanks again

                    Comment


                    • #40
                      Viewing processed data

                      Great program for processing data. I used it to find fold change and which genes had the greatest fold change between groups. I want to know if its possible to sort the data according to fold change and if I could view more than just the top six in the "head" display. Thank you much.

                      Comment

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