Conversation starter: common mistakes in population genetics

When interpreting the results, it is important to focus more on biological relevance than on statistical significance. That does not mean that significance is unimportant; results that have a straightforward interpretation but are not significant should not be considered. On the other hand, one should not be blinded by results that are strongly significant. In the genomics era, with thousands upon thousands of loci, strong significance is easily obtained even for biologically marginal processes.

Recently accepted to Molecular Ecology, Patrick Merimans’ “Seven common mistakes in population genetics and how to avoid them” was burning down the house on Twitter this past week.
I can definitely see why this sort of paper is both timely and interesting to a wide array of scientists. It’s a quick read, and sure to generate some discussion. One opinion I’ve seen popping up over and over is that this list is just the start of the common mistakes in population genetics, but I’ve seen fewer suggestions as to what actually needs added to the list.
So I ask you, opinionated readers, what mistakes are we making? Why keep them to yourself when you can share?
Meirmans, P. G. (2015). Seven common mistakes in population genetics and how to avoid them. Molecular Ecology.

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