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Old 08-30-2013, 03:06 PM   #1
Location: Seattle, WA

Join Date: Sep 2010
Posts: 17
Default Different normalization methods with count data

Hello folks, Quick question. I have RNAseq count data sets which I would like to analyze together. Experimentall they are similair they only differ by their depths of coverage . One set has about 30 million reads and the other has about 70 million. When you look at these files in an MDS plot you can see they are clearly different. Can anyone recommend a good aggressive normalization technique? Something similar to combat? I have tried the built in ones in DEseq and EDGER but would like to use one that's slightly more aggressive. Any suggestions are appreciated .thanks
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Old 08-31-2013, 02:05 AM   #2
Devon Ryan
Location: Freiburg, Germany

Join Date: Jul 2011
Posts: 3,478

Is it just the size normalization that's not really working sufficiently for you or are there other batch effects that you need to address (you mentioned combat, so I wonder about that)? It'd be helpful if you provided some more details and preferably a plot or two to demonstrate what's functioning poorly. You'll likely receive a higher quality of feedback then
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Old 09-01-2013, 05:27 AM   #3
Simon Anders
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Location: Heidelberg, Germany

Join Date: Feb 2010
Posts: 991

An MDS plot on raw count data is very unlikely to give any useful information. You should not use it for this purpose.
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