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  • uniportdb
    Junior Member
    • Jun 2011
    • 5

    #1

    CuffDiff: genes with highly abundant reads have FPKM 0.

    I just started learning rna-seq data anlaysis following Nature Protocols 7, 562–578 (2012).
    I used CuffDiff after tophat, but the genes with highly abundant reads have FPKM 0.
    I tried all the different normalization options in CuffDiff, and --max-bundle-frags 2000000, but still FPKM 0 for the genes with the largest number of mapped reads. Is there any upper bound like Microarray excludes the saturated spots ?

    I added example below,
    In sample A, it has FPKM 0, because it has the most number of reads, but the same gene in sample B has FPKM 3789, because it's in the confidence zone in sample B ? Please, help me to get FPKM for those genes with highly abundant reads. How can I get FPKM for PM_0405A60 from the example below?
    Thanks,


    Both examples below were sorted by the # reads in the descending order.
    I counted the number of reads using 'htseq-count'

    Sample A

    Gene | # reads | FPKM
    PYYM_0405060 | 1447079 | 0
    PYYM_1351050 | 675926 | 0
    PYYM_1007060 | 559162 | 0
    PYYM_1209040 | 421148 | 29315.7

    Sample: B
    Gene | # reads | FPKM
    PYYM_0501060 | 1633262 | 0
    PYYM_1351050 | 757339 | 0
    PYYM_0405060 | 552553 | 3789.85

    CuffDiff –verbose printed the below; PM_0405A60’s loci is PyYM_04_v1:214849-216007


    Inspecting bundle PyYM_04_v1:206968-210685 with 5956 reads
    Inspecting bundle PyYM_04_v1:211950-212458 with 368 reads
    Inspecting bundle PyYM_04_v1:213051-213787 with 2864 reads

    Inspecting bundle PyYM_04_v1:214849-216007 with 943663 reads

    Inspecting bundle PyYM_04_v1:218737-223186 with 746 reads
    Inspecting bundle PyYM_04_v1:223748-224267 with 889 reads
    Inspecting bundle PyYM_04_v1:225620-226957 with 399 reads
    Inspecting bundle PyYM_04_v1:227958-238759 with 10900 reads
    Last edited by uniportdb; 02-18-2013, 04:50 PM.
  • paulk
    Junior Member
    • Nov 2010
    • 4

    #2
    I encountered something like this last year, where I was getting transcripts flagged as HIDATA in Cufflinks output.

    You might try increasing the --max-bundle-frags setting in from its default setting to get around this issue. See:

    --max-bundle-frags <int> Sets the maximum number of fragments a locus may have before being skipped. Skipped loci are listed in skipped.gtf. Default: 1000000

    Paul Krzyzanowski
    Blog: www.checkmatescientist.net

    Comment

    • kadircaner
      Member
      • Jun 2011
      • 13

      #3
      I'm having the same problem but in my case there are no genes in the skipped.gtf file, so it's not because of HIDATA flag but there is another problem that I couldnt figure out yet... Any help would be really appreciated!!

      Comment

      • uniportdb
        Junior Member
        • Jun 2011
        • 5

        #4
        Thank you, PaulK.

        I tried --max-bundle-frags 2000000, but still 0 FPKM.
        And then I tried --max-bundle-frags 3000000, at last I have none-zero FPKM 107219.
        I guess it's paired-end, so the max should be > 2 * No. reads.
        Last edited by uniportdb; 02-18-2013, 04:59 PM.

        Comment

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