Hi,

We have run a pilot RNA-Seq study and I used `edgeR` package to obtain differential expression results. The results output a `gene column` along with the `logCPM`, `logFC` and `p-value` column. I have a question regarding conversion of log2 scale data to linear data for certain analysis. How can this be accomplished. Is there any R package to do this?

For instance, can I use the base function in R like below:

    Linear FC value = 2^(logFC)
    
    Linear CPM value = 2^(logCPM)

Thank you,

Toufiq
All results output from edgeR are on a log-2 scale, so yes you can unlog the logFC and logCPM values using the formula you give (as @rpolicastro already confirmed in his answer).

Let me say philosophically though that I don't agree that unlogged values can be described as "linear". Expression results are usually best analysed on a log scale and unlogged values do not behave in a linear fashion for most purposes.

Note it is especially important not to try to undo edgeR's logFC moderation, as mediated by the prior.count values, if you are working on an unlogged scale. If you really did want unmoderated fold-changes then you would simply set `prior.count=0` in the call to `exactTest` instead of doing your own ad hoc hacking. I can't imagine how that could be a good idea however. Getting infinite fold-changes from tiny counts (0 vs 1 for example) does not help anyone.