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You could implement an approach like the one described in this paper: http://www.ploscompbiol.org/article/...l.pcbi.1000598 in order to estimate the background RPKM/FPKM and arrive at a cutoff. It's based on looking at false positive and false negative rates based on a set of known genes and a set of control regions for which there is no evidence that they are being expressed. -
FPKM/RPKM cut-off question
I have got FPKM and some genes have really low FPKM and I am going to do stat analysis for all the genes; my question is the analysis should be like microArray analysis and need some cut-off numbers? any suggestion for this?
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Innovations in next-generation sequencing technologies and techniques are driving more precise and comprehensive exploration of complex biological systems. Current advancements include improved accessibility for long-read sequencing and significant progress in single-cell and 3D genomics. This article explores some of the most impactful developments in the field over the past year.
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