**0**wrote:

I have a data set with loge base expression values of 90 normal and 10 tumor sample.

*mydesign<- cbind(Tumor=c(rep(1,90),rep(0,10)),Control=c(rep(0,90),rep(1,10)))*

Now, I proceeded with two way:

*fit <- lmFit(data, design=mydesign)
fit <- eBayes(fit)
topTable(fit)*

*numGenes <- nrow(data)
case1.list <- topTable(fit,number=numGenes)*

or

*cont.matrix <- makeContrasts(TumorvsControl=Tumor-Control, levels=mydesign)
fit2 <- lmFit(data, design=mydesign)
fit2 <- contrasts.fit(fit2, cont.matrix)
fit2 <- eBayes(fit2)*

*case2.list <- topTable(fit2,number=numGenes)*

However, when i searched for a particular gene, the results are quite contrasting. e.g.

case1.list["ENSG1",]

Tumor Control AveExpr F P.Value adj.P.Val

ENSG1 1.53268 5.134342 1.87246 1802.497 1.115791e-83 4.074213e-83

case2.list ["ENSG1",]

logFC AveExpr t P.Value adj.P.Val B

ENSG1 -3.601662 1.87246 -29.42565 2.183333e-53 3.353327e-49 110.5354

Could anyone please advice that with given tumor and control estimation, how log FC were obtained?

"contrast" in limma means something similar to "What conditions I want to compare" .

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