Question: Why does limma voom E value give different result than the voom object
0
gravatar for Ahdee
5 weeks ago by
Ahdee40
United States
Ahdee40 wrote:

Hi so I notice something interesting.

data <- voom(x, plot=T, design = design2) 
vfit <- lmFit(data)
vfit <- eBayes(vfit)
topTable(vfit,coef=2,sort.by="P")

vfit <- lmFit(data$E, design = design2)
vfit <- eBayes(vfit)
topTable(vfit,coef=2,sort.by="P")

The two results above gives slightly different p value - very slightly but enough that the top10 from topTable gets shuffle a bit. Does anyone know why that is the case? thanks!

limma voom rna-seq • 90 views
ADD COMMENTlink modified 5 weeks ago by thokall160 • written 5 weeks ago by Ahdee40
Answer: Why does limma voom E value give different result than the voom object
1
gravatar for thokall
5 weeks ago by
thokall160
Swedish Museum of Natural History
thokall160 wrote:

The difference between your two examples are that you are using the complete Elist object from the voom function in the former and only the E slot of the same list in the later. By using only the normalized expression values you are not using all information from the voom function (see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053721 ). The weights can be used in the linear modelling, but it will also work without them. Without the weights the results can of course be different.

ADD COMMENTlink modified 5 weeks ago • written 5 weeks ago by thokall160

@thokall oh yes that right. I read it more carefully now whereby I thought previously that the E value were not only normalized but weighted as well, my bad, thanks!

ADD REPLYlink written 5 weeks ago by Ahdee40
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