Multi-ancestry genome-wide association study of severe pregnancy nausea and vomiting Nature Genetics - Multi-ancestry GWAS meta-analysis identifies risk loci for severe nausea and vomiting of pregnancy. Downstream analyses explore maternal and fetal contributions of these loci and...

Thrilled to see this out. What started out as a chat several years back with @drfejzo.bsky.social about leveraging publicly available data on hyperemesis gravidarum GWAS turned into a wonderful collaboration with April Shu, @mvaudel.bsky.social, @xwww.bsky.social and many others!

rdcu.be/fdl9k

If you use dim. reduction, you may be interested in two recent preprints we've posted on contrastive PCA:
The Rayleigh Quotient and Contrastive Principal Component Analysis I & II
w/ Maria Carilli & Kayla Jackson. They cover a lot of ground from theory to practice. 1/🧵

Very proud to share our new work on General, orders-of-magnitude faster whole-genome analysis with genotype representation graphs (GRG). We topped ourselves in this one 🚀 and made GRG a practical foundation for biobank-scale population and statistical genetics. www.biorxiv.org/content/10.6...

Good to know lol

Another preprint from our group @mdanderson.bsky.social led by talented postdoc @seantbres.bsky.social! Joint with @jonhuang.bsky.social, exploring the intersection of environmental toxins, maternal/fetal health, and placental txomics. Tweet thread below!

I used a combination of claude and codex, as well as the excellent base code from our jaxQTL project, to drive glmax. glmax is a jax-based GLM framework that is jit-compiled and end-to-end differentiable.

It leverages implicit function theorem for improved autodiff.

mancusolab.github.io/glmax/

Here's our R package for interacting with WGS derived GWAS summary statistics with many rare variants (from e.g. UKB or AofUs). It uses duckdb underneath so it's fast. Includes some helpful tie ins to Open Targets / Encode Screen / Ensembl APIs for annotation. weinstocklab.github.io/gwasplot/ind...

The dynamic duo

LoL child won’t lie :)

GitHub - mancusolab/jax_ldsc Contribute to mancusolab/jax_ldsc development by creating an account on GitHub.

I used my JAX-based skills for codex to port the excellent Python3 LDSC spec to JAX and Polars.

My intent here was to stress test my JAX skill definitions and find how I could improve rules and contexts--NOT to develop a replacement github.com/mancusolab/j...

Yeeess! Foot on table leaning back

Been trying my hand with agents with varying degrees of success and placed some definitions into a repo.

Feel free to fork/pull-req for improvements. I want to get a skill in there to generate code -> latex (and vice versa) for validation soon.

github.com/quattro/jax-...

hijack def adds fear of flying…very good show

😂 mental breakdown within an hour lol

🤩🤩

Integrating perturbational screens, eQTL, and GWAS data identifies mediating genes for complex traits Most current GWAS-eQTL approaches prioritize genes whose mediating effects on complex traits act through cis-regulation, while trans-acting genes remain largely underexplored. Recent perturbational sc...

Happy to share our new preprint from @sashagusevposts.bsky.social and @nmancuso.bsky.social labs! We introduce Mr. PEG, a framework integrating perturbational screens, eQTL, and GWAS data to identify mediating genes for complex traits. (1/n) www.medrxiv.org/content/10.6...

LoL now I wanna add it to my watchlist

Ah that’s why. I was confused for a sec when I pulled the branch earlier this morning and run it with —mode and —model. 😂

You got the bags! One step at a time :)

Genetic prediction with ARG-powered linear algebra Ancestral recombination graphs (ARGs) are an attractive means for quantitative genetic analysis of complex traits because they encode the realized genetic relatedness between a sample of individuals i...

www.biorxiv.org/content/10.1...

We finally submitted the earlier preprint to a journal after massive restructuring.
We've expanded the REML section for those interested in the method. We clarify that ARG-LMM estimates mutational variance and not additive variance.

How do genetic association studies rank genes? Genome-wide association studies and rare-variant burden tests reveal complementary aspects of trait biology.

@hakha.bsky.social and I wrote a Research Briefing (with a lay summary + "behind the scenes") of our paper on how genes are prioritized by GWAS and rare variant burden tests. 🧬🧪

www.nature.com/articles/d41...

Looking forward to presenting our work on characterizing eqtl architecture across ancestors and cells tomorrow at the Evolgenome seminar!

Huge thanks for the invite @lindakachuri.bsky.social

That will explain many GWAS hits

Specificity, length and luck drive gene rankings in association studies - Nature Genetic association tests prioritize candidate genes based on different criteria.

How do GWAS and rare variant burden tests rank gene signals?

In new work @nature.com with @hakha.bsky.social, @jkpritch.bsky.social, and our wonderful coauthors we find that the key factors are what we call Specificity, Length, and Luck!

🧬🧪🧵

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

Very proud of you @tszfung.bsky.social for so many achievements!! 🎊

His Dudeness

Simple scaling laws control the genetic architectures of human complex traits Genome-wide association studies have revealed that the genetic architectures of complex traits vary widely. This study shows that differences in architectures of highly polygenic traits arise mainly f...

Why do complex traits differ in their genetic architecture?
In our new PLOS Biology paper, we will try to convince you that two simple scaling laws drive differences in the number, effect sizes and frequencies of causal variants affecting complex traits.

Thread:
journals.plos.org/plosbiology/...