Report and compare log2FC vs FC
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@catalina-aguilar-hurtado-6554
Last seen 10 months ago
United States

Hi Michael,

I will like your opinion on reporting FC or log2FC. I use Deseq2 but other people I work with use other programs and report their data in FC so I usually convert my data to FC.

res$FC <- logratio2foldchange(res$log2FoldChange, base=2) 

Is there any reason why we should use one or the other? or is just a matter of personal likes?

Thanks

Catalina

 

deseq2 logfc • 16k views
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@ryan-c-thompson-5618
Last seen 12 months ago
Scripps Research, La Jolla, CA

I personally prefer log2 fold change, because of the symmetry: +1 is twofold up, and -1 is twofold down, etc. But many biologists are not comfortable thinking in log space and prefer just fold changes. Either way, it's the same information.

If you want to report non-log fold changes but still preserve the symmetry, you can convert "2" to "2-fold up" and "0.5" to "2-fold down".

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Hi Ryan thanks for your reply. Don't really understand how to preserve the symmetry, what do you mean by 2-fold up or down?

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I mean that "2-fold up" and "2-fold down" are conceptually of equal magnitude (i.e. symmetric), But their corresponding fold changes, 2 and 0.5, are not, while their corresponding log2 fold changes, +1 and -1, are.

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smoorthie ▴ 10
@smoorthie-7531
Last seen 6.5 years ago

If you are going to plot the data (as opposed to just quoting values) then I think Ryan's argument about symmetry is even stronger. Plotted naively a 100-fold up-regulated gene looks like a much bigger effect than a 0.01-fold down-regulated gene. Of course then the answer (if you have to quote fold changes rather than log2 fc) is simply to plot with a log-scale.

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