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Old 01-11-2017, 09:09 PM   #1
tedwong
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Location: Sydney

Join Date: Mar 2015
Posts: 13
Default Why should MA plot be flat after normalization?

I'm talking about the slide: http://bioinformatics.mdanderson.org...09/ma08_bw.pdf

In page 5, the title is "Why is Normalization an Issue?". The author compares the MA plot before and after normalization. He writes "Variation that is obscuring as opposed to interesting."

Q1: I can see the fitted red line before and after normalization. What's that red line?

Q2: Why is the second MA plot (after normalization) is better? The distribution is more symmetric, but what does that have anything to do with biological variation and statistical testing? Why should I care symmetry?

Last edited by tedwong; 01-11-2017 at 09:26 PM.
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