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Old 11-26-2014, 12:30 AM   #2
Devon Ryan
Location: Freiburg, Germany

Join Date: Jul 2011
Posts: 3,480

Typically one would normalize all of the samples together. You would also fit the entire dataset with a model rather than subsetting it (by year or treatment). While there are certainly occasions when this works poorly (generally when there's a large read number difference spread over a factor), it's generally the best course.

BTW, I hope you don't plan to run your own GLM. There are many prewritten tools, such as DESeq2 or edgeR that have additional features...and there's no point in reinventing the wheel.
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