Hi everyone,

I have a microarray set of 26933 genes and 6 samples (3 controls and 3 mutants). I calculated differential expressed genes using limma's topTable() function. I got a result of this format:

> head(res.new)

logFC AveExpr t P.Value adj.P.Val B 17291881 -2.157936 9.021125 -41.49770 3.218440e-09 3.829474e-05 10.82552 17357688 -2.364349 7.160051 -41.15755 3.397181e-09 3.829474e-05 10.79753 17224251 1.820522 10.665778 37.01446 6.816679e-09 3.829474e-05 10.41426 17239845 -2.025497 10.054660 -35.87667 8.366167e-09 3.829474e-05 10.29350 17304523 -1.830077 10.117184 -35.36567 9.191590e-09 3.829474e-05 10.23680 17229782 2.716749 7.911040 35.24054 9.407763e-09 3.829474e-05 10.22267

The logFC values are log2(FC). How do I convert the values *(positive and negative)* to normal fold changes?

I tried this:

#take 2^(absolute(log2FoldChange))

> res.new$FC<-2^(abs(res.new$logFC))

#change the sign of FC according to log2FC

> res.new$FC<-ifelse(res.new$logFC<0,res.new$FC*(-1),res.new$FC*1)

But I am not sure if I am correct. Please let me know.

Thanks!

Thanks a lot for this link. This is the new link to this package. Assuming that your data is loaded in "dataset", all that was needed to use it was:

Doing it using formula loses the negative values of logFC. I had earlier used the formula:

Using the above function I converted logFC to normal FC values for three groups(MC,SC,OC). I'd like to compare the normal FC values among these groups, how do I say this particular gene has expressed more in this particular group ?

I got very few differential expressed genes, with 1.5 Foldchange very few, can I consider 1.41 foldchange is this is acceptable ? suggestions please.