Hello,
After getting results from edgeR, How do I know which logCPM values are significant and which are not?
I know that we can calculate RPKM values through edgeR by using
gdrpkm<- rpkm(data,gene.length=vector)
Error in gene.length/1000 : non-numeric argument to binary operator
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written
by
kanika.151
You can ignore the logCPMs, they're not useful for you. Pretty much the best you can do with your dataset is to use GFOLD.
Ohk. hmm. How reliable is GFOLD? Are there any publications made using that software?
For unreplicated data it's about as reliable as one can hope. You might be able to find publications using it, though if I were the reviewer I'd reject all studies lacking replicates (I'm not alone in this).
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written
by
Devon Ryan
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Define "significant". logCPM values are logCPM values, there's no concept of significance typically attached to them.
My RNA Seq data does not have technical replicates as the data was pooled into one. That is no replicates which won't give conclusive results per say which is why I cannot take P value or FDR values into consideration. I wanted to know if I had to deduce from logCPM values which genes are differentially expressed and which are not how would I do that? As in which is significant and which is not?