GREML-WGS
Article
GREML-WGS is a recurring concept in the Astral Codex Ten archive, appearing 2 times across 2 issues between June 26, 2025 and December 03, 2025. The archive places it in contexts such as “we might be able to use a technique called GREML-WGS to get more definitive answers about rare variants”; “a whole-genome analysis technique called GREML-WGS”. It most often appears alongside British, Cremieux, IQ.
Metadata
- Category: Concepts
- Mention count: 2
- Issue count: 2
- First seen: June 26, 2025
- Last seen: December 03, 2025
Appears In
- Missing Heritability: Much More Than You Wanted To Know
- The Good News Is That One Side Has Definitively Won The Missing Heritability Debate
Related Pages
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- British (2 shared issues)
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- Cremieux (2 shared issues)
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- IQ (2 shared issues)
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- Sasha Gusev (2 shared issues)
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- Substack (2 shared issues)
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- Wainschtein (2 shared issues)
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- Aftab (1 shared issues)
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- Alex Young (1 shared issues)
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- Arthur Jensen (1 shared issues)
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- Awais Aftab (1 shared issues)
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- behaviorism (1 shared issues)
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- Biobank (1 shared issues)
External Links
Source Context
Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.
Are we going to find and cash out “rare variants and interactions” soon? If we don’t, how long should we wait for genetic science to advance before changing our mind and deciding we must be missing something more fundamental? Alex Young thinks that once we get enough whole genomes sequenced (probably soon!) we might be able to use a technique called GREML-WGS to get more definitive answers about rare variants. But other experts I talked to said that if complex interactions were a big part of the picture, this might be “computationally intractable”. On the other hand, “computationally intractable” is a relative term: with enough data, genomic language models offer the potential for improved understanding of nonlinear effects. I’m encouraged to see increasingly good discussion of these topics on Substack, Twitter, and elsewhere. People like Sasha Gusev and Eric Turkheimer deserve credit for opening the discussion, but I would like to see a robust back-and-forth with the other side. Thanks to everyone who helped me review this post, including Ruben Arslan, Alex Young, Damien Morris, and some other people who didn’t respond to my email asking if I had their permission to list their names publicly (if this is you, let me know and I’ll edit you in). Most of what’s valuable is theirs, and all errors are mine alone the fault of o3, which provided invaluable research assistance but also hallucinated constantly. 1I’m abbreviating “two percentage points” as 2%pp. Nitpickers complain if I don’t use the “percentage points” framing, but it’s too long to spell out each time. 2Geneticists distinguish between three related concepts: Polygenic score r^2 is the degree to which our current best genetic models can predict traits. You might use this to discuss the accuracy of a genetic test or an embryo selection procedure.
But as technology improved, funding increased, and questions about heredity became more pressing, geneticists finally set out to do the hard thing. They gathered full genomes - not just the 0.1% - from thousands of people, and applied a whole-genome analysis technique called GREML-WGS. The resulting study was published earlier this month as Estimation and mapping of the missing heritability of human phenotypes, by Wainschtein, Yengo, et al.