Hallo to everyone,

In have a  model  like the factorial design example in the limma user 
guide

TS <- factor(TS, levels = c("WT.U", "WT.S", "Mu.U", "Mu.S"))
design <- model.matrix(~0 + TS)
colnames(design) <- levels(TS)
cont.matrix <- makeContrasts(
 WT.SvsU = WT.S - WT.U,
 Mu.SvsU = Mu.S - Mu.U,
 Diff = (Mu.S - Mu.U) - (WT.S - WT.U),levels = design)
fit <- lmFit(eset, design)
fit2 <- contrasts.fit(fit, cont.matrix)
fit2 <- eBayes(fit2)

I am planning to extract the common response to the treatment between  WT 
and Mu  using nestedF

cont.matrix <- makeContrasts(
 WT.SvsU = WT.S - WT.U,
 Mu.SvsU = Mu.S - Mu.U)
fit <- lmFit(eset, design)
fit2 <- contrasts.fit(fit, cont.matrix)
fit2 <- eBayes(fit2)
results <- decideTests(fit2,method="nestedF",p=0.05)

and to extract the different response testing the interaction term with 
moderated t statistics 

cont.matrix <- makeContrasts(
  Diff = (Mu.S - Mu.U) - (WT.S - WT.U),levels = design)
fit <- lmFit(eset, design)
fit2 <- contrasts.fit(fit, cont.matrix)
fit2 <- eBayes(fit2)
toptable(fit2,adjust="BH")

and finally make a Venn Diagram with the results of the three comparisons

Is this approach correct to determinate which genes respond only in WT, 
which ones only in Mu and which, among the common ones, are differently 
expressed?

I would really appreciate some help

Thank you in advance

Massimo Acquaviva

Department of Molecular Biology
Giannina Gaslini Institute, Genova Italy













Aiutaci ad aiutare: Il tuo 5 per mille a sostegno della RICERCA.
Come fare: nella prossima dichiarazione dei redditi ti chiediamo di 
apporre la firma nel riquadro "Finanziamento agli enti della ricerca 
sanitaria" 
e il codice fiscale dell'Istituto Giannina Gaslini: c.f. 00577500101.
Istituto Giannina Gaslini - www.gaslini.org
.

	[[alternative HTML version deleted]]

