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  • NaN result with DEXSeq

    I'm having some trouble getting running DEXSeq. I generated count files using the python scripts and have gotten as far as trying to fit the dispersion function, which fails with an error:

    > a186Exons
    ExonCountSet (storageMode: environment)
    assayData: 170526 features, 4 samples
    element names: counts
    protocolData: none
    phenoData
    sampleNames: wt-1 wt-2 a186-3 a186-4
    varLabels: sizeFactor condition ... countfiles (5 total)
    varMetadata: labelDescription
    featureData
    featureNames: AT1G01010:001 AT1G01010:002 ... ATMG01410:001 (170526 total)
    fvarLabels: geneID exonID ... transcripts (13 total)
    fvarMetadata: labelDescription
    experimentData: use 'experimentData(object)'
    Annotation:

    > pData(a186Exons)
    sizeFactor condition replicate type countfiles
    wt-1 1.9951460 W 1 paired-end wt-1
    wt-2 1.2640540 W 2 paired-end wt-2
    a186-3 0.8502673 m 1 paired-end a186-3
    a186-4 0.5048640 m 2 paired-end a186-4

    > a186Exons=fitDispersionFunction(a186Exons)
    Error in if (sum(log(coefs/oldcoefs)^2) < 0.005) break :
    missing value where TRUE/FALSE needed
    In addition: Warning message:
    In log(coefs/oldcoefs) : NaNs produced
    I'm guessing the error (about missing values) is probably a result of the NaNs produced. estimateDispersions didn't give any warnings or errors. To be honest, I'm not even sure where the NaNs are coming from -- I'm guessing it's not a problem that there are exons with a zero count, right? I'm at a loss about what to try next, so I would be very grateful for a pointer in the right direction (or maybe even a solution). If some extra information would be helpful in sorting this out, please let me know.

    Thanks!

  • #2
    fixed!

    Hi!

    Thank you very much for the error report and from sending me your ecs object. I found the problem and its now fixed in version DEXSeq 0.99.3,
    it was a detail when dealing with NAs.

    Details, I did not know this happened in R:

    Code:
    > x <- rnorm(100, 0, 1)
    > x <- c(x, rep(NA, 2))  ## introduce some NAs
    > x[which(x < 0)] == x[x < 0]
     [1]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
    [13]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
    [25]  TRUE  TRUE  TRUE  TRUE    NA FALSE FALSE FALSE FALSE FALSE FALSE FALSE
    [37]    NA FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
    [49] FALSE
    Warning message:
    In x[which(x < 0)] == x[x < 0] :
      longer object length is not a multiple of shorter object length
    If there are NAs in a logical vector, subsetting in the below way does not work, a 'which' needs to be added

    Code:
    x[x < 0]
    Thanks again!

    Comment


    • #3
      Thanks very much for the quick fix! The Bioconductor website still lists version 0.99.2 (http://www.bioconductor.org/packages...ml/DEXSeq.html). Is there somewhere else to look for the new version or should I just wait for it to be updated there?

      Comment


      • #4
        You can get it directly from the bioconductor svn repository a indicated here:



        And install it manually!

        Comment


        • #5
          I've installed the fixed version of DEXSeq. But I get the same errors again.

          ecsExons <- fitDispersionFunction(ecsExons)
          Error in if (sum(log(coefs/oldcoefs)^2) < 0.005) break :
          missing value where TRUE/FALSE needed
          In addition: Warning message:
          In log(coefs/oldcoefs) : NaNs produced

          Comment


          • #6
            Thanks, areyes. I installed the new version and my problem is solved.

            Comment


            • #7
              This is an old thread and it seems the wiki link is broken now... is there another bioconductor svn how-to somewhere?

              thanks,
              Leda

              Originally posted by areyes View Post
              You can get it directly from the bioconductor svn repository a indicated here:



              And install it manually!

              Comment


              • #8
                Google "bioconductor svn repository":

                The Bioconductor project is maintained in a Git source control system. Package maintainers update their packages by pushing changes to their git repositories. This chapter contains several...

                Comment


                • #9
                  No need to use the SVN repository, anyway. Changes get propagated from the SVN repo to the downloadable packages within a few days, and this fix is several months old.

                  Comment

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