you heard this one?
www.youtube.com/watch?v=RS72...

Yeah I don't really get it. The hard part is getting the genetic estimates so running this across many other 23andme traits (even restricting to non-controversial traits) would have been very informative. Perhaps they're going to follow up with more detailed linkage analyses?

You can estimate the total genetic difference between populations without having to know the underlying causal variants. You don't get the mechanism and you still have to make strong assumptions on GxE and ascertainment, but IMO an effective way to prioritize traits for follow-up.

Yes, exactly, the idea was to overload the cells with many perturbations and then estimate components of higher-order interactions GREML-like. But we couldn't get enough cells with multiple edits and only had power to look at module interactions.

www.nature.com/articles/s41...

We were hoping to look at this in perturb-seq data, but very hard to get the number of combinatorial effects needed for statistical power.

I think about this every time I shave:

very relevant, thank you!

That's a great idea, and looks something like the below. I'm working on the size scaling a bit more to convey the point more clearly

Yeah I was thinking about this initially and unable to find any examples in the literature where epistasis tagged by additivity versus "pure" additivity mattered. I think the response really is just about narrow-sense h2 (as in the Breeder's Equation).

Nice blog and good to see this also from the twins/shared environment side. We (with my colleagues in @wittbrodtlab.bsky.social) have tried to tackle the non-additive in experimental settings (in medaka fish) which we can map to human (as the medaka fish are "wild") www.biorxiv.org/content/10.1...

Yeah, uncentered effects make more sense to me biologically but of course you could design a statistical generative model where the interaction is purely non-additive.

great commentary article (and thanks for the thread!)

Yeah, in general multi component models will only take the part of the interaction that is not captured by additivity. The twin ADE model partitions them correctly but ONLY if there's no shared environment (and other assumptions hold).

Sure thing, see this gist. Note that this is always the affect allele frequency and not the minor allele frequency and there's no genotype scaling. Let me know if you think there's a better presentation.