Question: Why does limma voom E value give different result than the voom object
0
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
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
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.