Hello,
I am trying to replicate the DEG as performed in a RNA-Seq study. The steps below are exactly what the authors have mentioned in their methods section.
I have 8 cases and 20 controls (clinical data). I have taken the mean normalized expression for each gene in the control, and divided the normalized counts in the cases individually by sample using control mean to get the fold change.
Now I want to know if the fold change is significant or not. The authors have seemed to have performed a Mann-Whitney test. However, I am not sure how the authors went about this. Their results have individual p-values for each gene. I am not sure how to do that as wilcox.test gives an overall p-value (which is significant actually) when I use the mean case vs mean control normalized counts.
Could it be, that the authors just performed a Mann-Whitney test on the normalized expression values per gene? Its basically similar to a t-test, where you have two population of values. In this case one population would be the normalized expression values of the 20 control cases and the second population would be the normalized expressen values of the 8 cases, per gene.
Yes, I think so too. And looks like they used rankSumTestWithCorrelation from limma.
I will be following this example from Gordon Smyth. I am not sure how to know if I am right or wrong though. Maybe compare with the actual data they have shared. I'll update on how it goes.
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The best way to approach this would be to email the authors.
They aren't very responsive :'( I had to email them several times just for their raw counts data :'(
How recent is the paper? Unfortunately, if authors are not open to others reproducing their results, you will face such barriers. Keep at it, maybe future replies will be faster. If not, see if you can switch papers without compromising on your goal.
This year in June!
And thank you! I don't feel as disheartened as before :)
Hello Cookie-san!
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