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Old 11-21-2014, 08:52 AM   #11
dpryan
Devon Ryan
 
Location: Freiburg, Germany

Join Date: Jul 2011
Posts: 3,480
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I would say yes, the flatter the coverage the more likely it is to be real.

Regarding RPKMs, you just need the gene (or other feature) lengths. I'm pretty sure I've posted a script to take a GTF and output union gene model lengths before. I'll have to look around for it (if nothing else, I'll just post it to github). You can then divide the normalized counts by those values and then divide by a million and you'll have RPKM (or FPKM if you used paired-end reads).
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