Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • herstein
    Junior Member
    • Oct 2011
    • 4

    Cufflinks 0 FPKM values

    Hi,

    We are running tophat/cufflinks on 3 identical human rna samples which were sequenced in 3 different lanes on 2 different flowcells. All 3 samples are from the exact same library.

    When running cufflinks, the genes.fpkm_tracking file for one sample is showing some genes with 0 FPKM and status FAIL, however these same genes in the other two samples are showing a non-zero FPKM.

    We are using tophat-1.4.0, bowtie-0.12.7, and cufflinks-1.3.0

    We ran tophat with the -G option and provided the gtf file. We ran cufflinks with -G option providing the same gtf file that we gave to tophat. We also ran cufflinks with -u -N --compatible-hits-norm -b hg19_ucsc.fa

    We've tried running without options -N and --compatible-hits-norm but still had the same results.

    We are confused how with 3 identical samples, one shows up with 0 FPKM but the other two seem to have valid FPKM's. For the 0-FPKM gene, we checked the bam file in IGV and it is definitely mapped.

    Has anyone encountered a similar problem or does anyone have any insight into this?

    Thanks!
    --Jennifer
  • letusgo
    Member
    • Aug 2011
    • 17

    #2
    Hi,
    Have you solved this problem yet? I met the same problem now.

    Comment

    • jp.
      Senior Member
      • Jul 2013
      • 142

      #3
      I also have same problem. I got only few genes with 0 FPKM value.
      I mean, control vs treated; control has 0 FPKM but treated shows 1098.13 FPKM.
      Theoretically speaking, it has very high fold increase, but cuffdiff Inf ?????
      do I have to include it or exclude. I think, this is very significant expression ????
      Can you all tell me please ?

      Comment

      Latest Articles

      Collapse

      • GATTACAT
        Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
        by GATTACAT
        Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
        07-01-2026, 11:43 AM
      • SEQadmin2
        Nine Things a Sample Prep Scientist Thinks About Before Sequencing
        by SEQadmin2


        I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.

        Here are nine questions we think about, in roughly the order they matter, before...
        06-18-2026, 07:11 AM

      ad_right_rmr

      Collapse

      News

      Collapse

      Topics Statistics Last Post
      Started by SEQadmin2, Today, 11:05 AM
      0 responses
      6 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 07-02-2026, 11:08 AM
      0 responses
      28 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 06-30-2026, 05:37 AM
      0 responses
      25 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 06-26-2026, 11:10 AM
      0 responses
      25 views
      0 reactions
      Last Post SEQadmin2  
      Working...