Hello, I want compare GE from experiment A (three replicates) with experiment B (three replicates)

Here is my workflow:

```
library(limma)
celFiles <- list.celfiles(path_to_cel_files,full.names=TRUE)
affyExpressionFS <- read.celfiles(celFiles)
eset <- rma(affyExpressionFS, background = TRUE, normalize = TRUE)
stress <- c(1,1,1,0,0,0) # first three replicates (case)
control <- c(0,0,0,1,1,1) # last three replicates (control)
design <- cbind(stress, control) # first term is numerator, second denominator of the ratio
fit <- lmFit(eset, design)
cont.matrix <- makeContrasts(STvsCO=stress-control, levels=design)
fit2 <- contrasts.fit(fit, cont.matrix)
fit2 <- eBayes(fit2)
tab <- topTable(fit2, adjust = "BH", confin =T , number = 1000, sort.by="logFC")
```

The problem is, that the highest absolute logFC value is 1.4 which seems very low. Which logFC values are normal for such comparisons?

My top candidates look like this:

```
ID logFC AveExpr t P.Value adj.P.Val B
8047174 1.410216184 8.394967474 3.253590303 0.012932418 0.596479114 -2.705225672
8126784 1.281783565 5.991972071 3.246829585 0.013058101 0.596479114 -2.711771396
```

Thank you

May I ask what do you like compare in both the experiments?

If you would like to compare genes that are significantly deferentially expressed in both the experiments, you may consider filitering the data based on significance... P Value...

thats the next problem. After multiple testing correction no gene is significant.