**10**wrote:

Daer Forum,

I want to get an estimate of the pairing variable BioReplicate

What I would do when using linear model is:

x1<-rnorm(10) x2<-1+rnorm(10) # Now create a dataframe for lme myDat <- data.frame(c(x1,x2), c(rep("x1", 10), rep("x2", 10)), rep(paste("S", seq(1,10), sep=""), 2)) names(myDat) <- c("y", "Condition", "BioReplicate") anova(lm(y ~ Condition + BioReplicate, data = myDat))

Which produces

`> `

`anova`

`(lm(y ~ Condition + `

`BioReplicate`

`, data = `

`myDat`

`))`

Analysis of Variance Table

`Response: y`

Df Sum Sq Mean Sq F value Pr(>F)

Condition 1 8.6975 8.6975 5.1585 0.04926 *

BioReplicate 9 5.8334 0.6482 0.3844 0.91470

Residuals 9 15.1744 1.6860

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

With limma, I am fitting :

`fit <- limma::lmFit(grp2$getNormalized()$data, `

model.matrix(~ Condition + BioReplicate, grp2$annotation_)`)`

`fit.eb <- limma::eBayes(fit)`

limma::topTable(fit.eb)

But topTable produces an output similar to that of `summary`

`.lm`

why I am looking for an output similar to `anova.lm.`

I wish everyone a beautiful day

regards

Witek