Hi.
Thank you for your answers. I already have the latest version of user guide.
I understand that the procedure in 9.5.2 is the recommended one (single factor), but I am required to perform two way anova.
For example, if I extract nomalized intensities of one probe, I can perform a two way anova for that probe:
>mat
data Strain Treatment
1 15087.105 WT U
2 13930.749 WT U
3 16495.873 WT U
4 13829.101 WT U
5 12628.449 WT S
6 10274.768 WT S
7 11306.912 WT S
8 11842.572 WT S
9 16296.351 Mu U
10 17066.216 Mu U
11 15817.936 Mu U
12 15001.087 Mu U
13 9952.837 Mu S
14 12524.801 Mu S
15 10785.661 Mu S
16 13326.560 Mu S
> res.aov=aov(data~Strain*Treatment,data=mat)
> summary(res.aov)
Df Sum Sq Mean Sq F value Pr(>F)
Strain 1 1806283 1806283 1.273 0.281
Treatment 1 59605572 59605572 41.998 3.02e-05 ***
Strain:Treatment 1 1156486 1156486 0.815 0.384
Residuals 12 17031010 1419251
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
it is right? I need to obtain the associated F and p-values of strain, associated F and p-values of treatment and associated F and p-values of interaction effect in the same way that they are obtained from the aov function, using limma and its moderated F statistics. I understand that with topTable(fit2,coef=2:4) I get the results of global or omnibus F test (I'm not interested in that test).
I understand that I should use the classic interaction model (9.5.4 section):
> design <- model.matrix(~Strain*Treatment)
(Intercept) StrainWT TreatmentU StrainWT:TreatmentU
1 1 1 1 1
2 1 1 1 1
3 1 1 1 1
4 1 1 1 1
5 1 1 0 0
6 1 1 0 0
7 1 1 0 0
8 1 1 0 0
9 1 0 1 0
10 1 0 1 0
11 1 0 1 0
12 1 0 1 0
13 1 0 0 0
14 1 0 0 0
15 1 0 0 0
16 1 0 0 0
> fit <- lmFit(eset, design)
> fit2 <- eBayes(fit2)
How to continue?
You should read the limma User's Guide that comes with the version of the limma package you are using. Or else the latest version of the Guide is always available from:
https://bioconductor.org/packages/release/bioc/vignettes/limma/inst/doc/usersguide.pdf
Your reference to Section 8.7 suggests that you are reading a limma User's Guide from many, many years ago.