Hi all,
I've experienced a similar problem: I used Cufflinks 2.0.0 with the aim of fixing the problem of too many FAIL results (~30%) derived by the version 1.3.0. The results was that roughly one hundred transcripts were DE and all the others had zero values. As reported in the webpage of Cufflinks from the release 2.0.1 this problem should have been fixed . So I launched the last version 2.0.2 retrieving the same results of the 2.0.0: only 134 transcripts DE and all other with zero FPKM. From my personal experience the 1.0.3 is the last release that not gives strange results (although it gives a lot of false positive). Since them all subsequent releases that were supposed to give improvements miserly FAIL :-)
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I'm having this same issue. Did you find a solution/did using an older version of cufflinks work for you?Originally posted by SeekRNA View PostI'm using cufflinks to compare expression in two conditions from modEncode BAM files. The FPKM values for both sets are zeros for every gene! There do not appear to be any errors (all are OK). What sorts of things give rise to this?
Thank you so much, and apologies if this is trivial as I am new to RNAseq
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I had a similar problem when using v.2.0. Going back to a previous version helped. Although since that time I have discovered different problems with my original data (it was improperly filtered) thus it is possible that my cufflinks problem was due to the data and not the cufflinks version. Never-the-less if you are running v.2 then you may wish to try a different version.
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Cufflinks giving all 0's
I'm using cufflinks to compare expression in two conditions from modEncode BAM files. The FPKM values for both sets are zeros for every gene! There do not appear to be any errors (all are OK). What sorts of things give rise to this?
Thank you so much, and apologies if this is trivial as I am new to RNAseq
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The immune system’s power comes from its genetic diversity, allowing myriad threats to be neutralized through first recognizing foreign antigens. That diversity is also what makes the immune system so difficult to study. Recent advances in sequencing technology and computational biology, however, are giving researchers new tools to understand immune responses and immune-related diseases in greater detail.
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