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  • CummeRbund csDendro error: "need finite ylim values" when replicates=TRUE

    All,

    I was trying to create a dendrogram (including replicates) in cummeRbund using the csDendro function, but I get an error stating: "Error in plot.window(...) : need finite 'ylim' values". I'm using the following command:

    Code:
    cuff<-readCufflinks()
    dend.rep<-csDendro(genes(cuff),replicates=T)


    Does anyone know why?

    Useful information:
    • I'm using R 2.15.1, tophat2 2.0.3, cufflinks 2.0.2, and cummeRbund 1.99.2
    • I have been following the protocol from Nature Protocols (http://www.nature.com/nprot/journal/....2012.016.html), but I'm getting a lot of NOTEST results (49,956) from cuffdiff. I'm currently awaiting results from two test runs testing '-c 0' and '--min-outlier-p 0' to see if that helps with the NOTEST results and to see if it's related to the above cummeRbund error. I'm testing these parameters as per Cole Trapnell's suggestions (http://seqanswers.com/forums/showthr...merbund&page=2)
    • I have two conditions with 30 and 23 replicates (mostly biological but a few technical)


    Thanks for your help!
    Last edited by mebbert; 07-18-2012, 10:29 AM. Reason: Modified the NOTEST number

  • #2
    Hi mebbert,

    Can you tell me if the output of:

    Code:
    repFpkmMatrix(genes(cuff))
    contains any missing values? I'm trying to figure out if this is the problem. Several users have had this problem.

    Thanks in advance,

    Cheers,
    Loyal

    Comment


    • #3
      Thanks for the response, Loyal. In short, yes there are missing values. Here's partial output from:

      Code:
      x<-repFpkmMatrix(genes(cuff))
      head(x)
      You will see that XLOC_000006 has only NA values. When looking at the first 30 rows there are two such situations.

      Code:
                  FFPE_0 FFPE_1 FFPE_2 FFPE_3 FFPE_4 FFPE_5 FFPE_6 FFPE_7    FFPE_8 FFPE_9 FFPE_10 FFPE_11 FFPE_12 FFPE_13 FFPE_14 FFPE_15 FFPE_16 FFPE_17 FFPE_18 FFPE_19 FFPE_20 FFPE_21 FFPE_22 FFPE_23
      XLOC_000001      0      0      0      0      0      0      0      0 0.0000000      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0
      XLOC_000002      0      0      0      0      0      0      0      0 0.0000000      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0
      XLOC_000003      0      0      0      0      0      0      0      0 0.0000000      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0
      XLOC_000004      0      0      0      0      0      0      0      0 0.0000000      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0
      XLOC_000005      0      0      0      0      0      0      0      0 0.0726539      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0
      XLOC_000006     NA     NA     NA     NA     NA     NA     NA     NA        NA     NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      NA

      Comment


      • #4
        Hi Mebbert, that's what I figured. This is something that will have to be fixed in the next release of cummeRbund and cuffdiff. Can you confirm that you are using cufflinks v2.0.2 as well?

        Thanks,
        Loyal

        Comment


        • #5
          Yes, I am using Cufflinks 2.0.2. Do you know if there is an estimated release date? Could this be related to the high number of NOTESTS that I'm seeing from CuffDiff?

          I should point out that I get the following warnings when I read in the data with readCufflinks():

          Warning messages:
          1: Removed 32139 rows containing missing values (geom_point).
          2: Removed 30203 rows containing missing values (geom_point).
          3: Removed 37458 rows containing missing values (geom_point).
          Furthermore, as per Cole Trapnell's advice (HERE), I reran the data with '-c 0' and '--min-outlier-p 0' in two separate analyses. NOTESTS decreased to 32137 with the '-c 0' option and did not change with '--min-outlier-p 0'.

          Any ideas?

          Thanks!
          Last edited by mebbert; 07-19-2012, 01:43 PM.

          Comment

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