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  • FPKM interpretation

    Hi all!

    I am analyzing differential isoform expression between some samples. I run Cuffdiff2 and i found the differentially expressed isoforms. I also calculated the porportion of the expression of each isoform compared to the expression of the gene (the sum of the expressions of all the isoforms of that gene). Now I need to better filter my results. I was thinking to focus on the highly expressed isoforms and on those with a relevant proportion, but I couldn't find a criteria to choose a cutoff based on the FPKM. When can I say that a gene or isoform is highly expressed? And how can I understand when a proportion is relevant? I would think that the relevance of the proportion depends also on the total expression, i.e an isoform which account for the 30% of an highly expressed gene might be not as relevant as an isoform which account for the 30% of a low expressed gene, am i correct?
    I had a look to related posts in this forum and to several articles but i couldn't find a clear guidline. Maybe the answer is not simple but if you could suggest me some statistical approach to analyze these data would be great.
    Thanks in advance!

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