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  • a11msp
    Member
    • Jun 2010
    • 26

    #1

    A stats question about DESeq

    It may be a slightly outdated question now that GLM-based testing is preferred to the exact test, but I'm just very curious...

    In the 2010 Genome Biology paper (http://genomebiology.com/2010/11/10/r106), formula 14 describes how in the negative binomial test, variance of condition A is estimated under the null hypothesis of the equality of per-condition means:

    σˆ2_{A} = ∑{all_j∈A} [ s{j}*q0+s{j}ˆ2 * v{A}(q0) ],

    where:
    ∑{all_j∈A} is the sum across all samples in condition A,
    s{j} are scaling factors for each of these samples,
    q0 is the pooled mean estimate,
    v{A} is the raw variance estimate for condition A given the mean.

    However, looking at the DESeq code, I'm not sure v{A} is actually estimated based on q0. Rather, it seems to me it is estimated based on q{A} - the observed mean of counts for condition A.

    Am I getting it wrong or there have been some changes that I'm not aware of?

    Thanks very much!
  • Simon Anders
    Senior Member
    • Feb 2010
    • 995

    #2
    If I am still read my old code correctly, then the variance-mean relation for condition A is fitted by a local regression of the per-gene variances onto the mean of the counts only from condition A (in the code for the estimateDispersion method, 'if' clause for 'per-condition': bmv$baseMean, where bmv is calculated from only the columns for the current condition), but to get the fitted value, this function is then evaluated for the overall mean (in the code: overall_basemeans). This is consistent with what we wrote in the paper, I think.

    However, in DESeq2, we now dropped the "per-condition" mode, because it was a bit difficult to reconcile with our general improvements to the dispersion estimation.

    Comment

    • a11msp
      Member
      • Jun 2010
      • 26

      #3
      Thanks a lot for your reply Simon!

      Comment

      • a11msp
        Member
        • Jun 2010
        • 26

        #4
        Sorry, one more question... Am I right then that for sharing mode == "maximum" and method == "per-condition", the maximum is computed between the fitted SCV given the overall mean and the observed SCV given the mean for a given condition?

        Many thanks!
        Last edited by a11msp; 10-15-2013, 08:02 AM.

        Comment

        • Simon Anders
          Senior Member
          • Feb 2010
          • 995

          #5
          Just looked through my code again. Yes, this is what I've put there. The reason, If I remember correctly, had something to do with the handling of zeroes.

          Comment

          • a11msp
            Member
            • Jun 2010
            • 26

            #6
            OK, thanks!

            Comment

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