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Excited to see our work published! I enjoyed a lot in this project and enjoyed even more (should I say this? 😃) from two very helpful and constructive reviewer comments! Thanks to all my coauthors; this is an amazing team work!

Excited to finally throw our hat in the ring. Here is our new method (named X-Wing) for cross-ancestry PRS. A key takeaway is that we now do EVERYTHING with sumstats alone which is a major methodological advance. Work is led by Jiacheng Miao & Hanmin. biorxiv.org/content/10.110…

Don't know you, but I'm more excited about the posters than the talks. Looking forward to many inspiring conversations and discussions! #ASHG2022 #poster

Preprinted in time for #ASHG2022! Happy to share Zijie Zhao's new work. We present PUMA-CUBS which advances PRS benchmarking & optimization. We can now fine-tune any PRS models and even do ensemble learning to combine models using GWAS sumstats alone! biorxiv.org/content/10.110…

You'll want to check out Jiacheng Miao's new paper if your work involves gene-environment interaction. This is our best GxE work so far. We introduce a statistical framework named PIGEON to reimagine how GxE studies could and should unfold. biorxiv.org/content/10.110…

New preprint from my group led by Yuchang Wu Zhongxuan(John) Sun. Almost every recent Alzheimer's GWAS combines clinical AD diagnosis and proxy phenotypes based on parental health survey. We report major limitations in the current practices of GWAS-by-proxy (GWAX) biorxiv.org/content/10.110…

At Stanford for the IGSS conference. Interesting talks, lovely weather, and beautiful campus! I think I like this place.

Our paper on misleading biases in AD GWAS-by-proxy is published Nature Genetics. We identify the source of biases and explore strategies to reduce them Yuchang Wu Zhongxuan(John) Sun Paper📰: doi.org/10.1038/s41588… Software🧑‍💻: github.com/qlu-lab/GSUB Sumstats⬇️: qlu-lab.org/data.html

Four presentations from us this year, covering very diverse topics. Stop by and say hi🍷#ASHG24 #ASHG2024 1) Genetic effect heterogeneity Yuchang Wu 2) Genetics of partner choice @S5b6bY284u9qqoa 3) Perturb-seq/GWAS data integration Stephen Dorn 4) ML-assisted GWAS Jiacheng Miao

#ASHG24 Interested in how to reliably use AI/ML to accelerate genetic discovery? Stop by poster 4151 this afternoon to chat!

pain in using cloud computing: took 1 day 10 hours and 44 minutes to finish some analysis using AllofUs data, and I accidentally deleted the "environment" and all the results are gone forever ... 😭😭😭

One score to rule them all: regularized ensemble polygenic risk prediction with GWAS summary statistics biorxiv.org/cgi/content/sh… #biorxiv_genetic

Our new PRS paper is out! We introduce a method to create regularized ensemble PRS on GWAS sumstats. Individual-level data is no longer needed for sophisticated ensemble learning Zijie Zhao Stephen Dorn Paper📰:biorxiv.org/content/10.110… Software🧑‍💻:github.com/qlu-lab/PUMAS

My first co-author paper is now preprinted! With Zijie Zhao and Qiongshi Lu we introduce PUMAS-ensemble, a regularized ensemble PRS requiring only GWAS summary statistics and LD reference data as input. biorxiv.org/content/10.110…