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  • proteomania
    Member
    • Sep 2010
    • 11

    DESeq and GSEA with pre-ranked gene list

    Hi all,

    I've been using DESeq for my RNA-Seq differential expression analysis. Now I want to use the DESeq result to generate a ranked-list, which will be used as the input in GSEA. My question is: Should I rank the genes using the fold changes or using the q-values?

    Thanks.
  • Simon Anders
    Senior Member
    • Feb 2010
    • 995

    #2
    How to combine GSEA with RNA-Seq is still unclear and subject to ongoing research. We (and other groups, I suppose) are looking at a couple of options.

    If you want something now, try using the moderate log fold change that are now reported by the newest version of DESeq. This is not ideal, and I don't want to even say that it is statistically sound, but it is probably better than using p values or raw fold changes.

    Comment

    • hlestrella
      Junior Member
      • Sep 2011
      • 2

      #3
      DESeq and GSEA with pre-ranked gene list

      Originally posted by Simon Anders View Post
      How to combine GSEA with RNA-Seq is still unclear and subject to ongoing research. We (and other groups, I suppose) are looking at a couple of options.
      I'm also interested in using RNA-Seq differential expression results as a ranked list into GSEA. Any new thoughts since last August on more appropriately ranking the genes coming out of DE analysis for GSEA (or other gene enrichment analyses)?

      Comment

      • maxUlysse
        Junior Member
        • Jan 2014
        • 2

        #4
        Have you looked into SeqGSEA ?
        cf : http://bioinformatics.oxfordjournals...tu090.abstract

        Comment

        • apredeus
          Senior Member
          • Jul 2012
          • 151

          #5
          Originally posted by Simon Anders View Post
          How to combine GSEA with RNA-Seq is still unclear and subject to ongoing research. We (and other groups, I suppose) are looking at a couple of options.

          If you want something now, try using the moderate log fold change that are now reported by the newest version of DESeq. This is not ideal, and I don't want to even say that it is statistically sound, but it is probably better than using p values or raw fold changes.
          Hello Simon,

          since this is such an old post, I figured I'd ask if there were any advances on the issue - either from your group or anybody else?

          I've tried few things but I quite come up with a criterion about what's working and what's not. Is using Wald statistic in pre-ranked GSEA a bad idea?

          Thank you for any input in advance.

          Comment

          • apredeus
            Senior Member
            • Jul 2012
            • 151

            #6
            Originally posted by maxUlysse View Post
            Have you looked into SeqGSEA ?
            cf : http://bioinformatics.oxfordjournals...tu090.abstract
            This is good, but it kind of forces you to use their own differential expression analysis. I would like to stick with DESeq2, and then use the results in GSEA.

            Comment

            • turnersd
              Senior Member
              • May 2011
              • 115

              #7
              (Old post, but folks are still watching, still high google rank.)

              Comment

              • Michael Love
                Senior Member
                • Jul 2013
                • 333

                #8
                I haven't done any testing on what output is best for downstream set analysis. I recently wrote a post on Bioc support site on how to produce a discrete output (yes/no DE) from DESeq2 for use with the Bioc package goseq. Another option would be to use the moderated LFC or Wald statistic as a continuous signal.

                Comment

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