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  • kenosaki
    Member
    • May 2010
    • 27

    #1

    Estimation of expression levels

    Hi,

    I use RPKM for the estimation of expression levels from RNA-Seq data usually.
    Does anyone know the alternative method?
    In what cases, the alternative way would be better than RPKM?

    Thanks
  • Simon Anders
    Senior Member
    • Feb 2010
    • 995

    #2
    That depends very much on what you want to do with your estimated expression levels.

    Comment

    • kenosaki
      Member
      • May 2010
      • 27

      #3
      I'd like to look at,
      1) Global expression changes of genes between two groups of sample from different tissues. (like microarray experiment)
      2) The exons that specifically spliced in the differentially expressed genes of interest identified from 1)
      3) Possibly, putative exons of genes in either tissues.

      Comment

      • Simon Anders
        Senior Member
        • Feb 2010
        • 995

        #4
        Originally posted by kenosaki View Post
        1) Global expression changes of genes between two groups of sample from different tissues. (like microarray experiment)
        The crucial part is to use an appropriate method to assess the statistical significance of any differential expression you may see. See our tool, DESeq, or Robinson and Smyth's edgeR for statistical methods.

        Both tools want unnormalized, raw counts. they don;t work if you normalize to RPKM, and methods that use RPKM as input have less statistical power.

        2) The exons that specifically spliced in the differentially expressed genes of interest identified from 1)
        Several people (including us) are working on a proper statistical test for this, but nothing is out yet. Cufflinks (Trapnell et al.) gets you at least half the way.

        3) Possibly, putative exons of genes in either tissues.
        For discovery of new features, normalization is quite unimportant. Either it is there or it isn't. There is no background, after all.

        Simon

        Comment

        • kenosaki
          Member
          • May 2010
          • 27

          #5
          Thank you Simon,

          I found the very informative thread about RPKM.
          Discussion of next-gen sequencing related bioinformatics: resources, algorithms, open source efforts, etc


          Ken

          Comment

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