PhilGoetz comments on SRG 4: Biological Cognition, BCIs, Organizations - Less Wrong
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? I see mentions of stuff like dominance and interaction all the time; the reason people tend to ignore it in practice seems to be that the techniques which assume additive/independence work pretty well and explain a lot of the heritability. For example, height the other day: "Defining the role of common variation in the genomic and biological architecture of adult human height"
Seems like an excellent start to me.
It would be better than nothing. I am grinding one of my favorite axes more than I probably should. But those numbers make my case. My intuition says it would be hard to mine a few million SNPs, pick the most strongly associated 9500, and have them account for less than .29 of the variance, even if there were no relationship at all. And height is probably a very simple property, which may depend mainly on the intensity and duration of expression of a single growth program, minus interference from deficiencies or programs competing for resources.
"My intuition says it would be hard to mine a few million SNPs, pick the most strongly associated 9500, and have them account for less than .29 of the variance, even if there were no relationship at all."
With sample sizes of thousands or low tens of thousands you'd get almost nothing. Going from 130k to 250k subjects took it from 0.13 to 0.29 (where the total contribution of all common additive effects is around 0.5).
Most of the top 9500 are false positives (the top 697 are genome-wide significant and contribute most of the variance explained). Larger sample sizes let you overcome noise and correctly weight the alleles with actual effects. The approach looks set to explain everything you can get (and the bulk of heritability for height and IQ) without whole genome sequencing for rare variants just by scaling up another order of magnitude.