Lida Wang (@LD_matrix) header
Lida Wang (@LD_matrix) profile picture

Lida Wang

@LD_matrix

Postdoc @DanaFarber and @harvardmed | Biostat Ph.D @penn_state | Statistical genetics, functional genomics, data science

 Boston, MA
lidawangpsu.github.io/Lida/
Joined August 2020
  • Tweets45
  • Following417
  • Followers170
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Photo by Lida Wang (@LD_matrix)
An ASHG planner that doesn't suck (Claude): sashagusev.github.io/ashg-20…
Image from Sasha Gusev (@SashaGusevPosts)
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New work from Pasi A. Jänne, us, and 23andme; led by Jackie LoPiccolo and Steven Micheletti. Characterizing a highly penetrant germline founder mutation for lung cancer.
Science Magazine (@ScienceMagazine) profile pictureScience Magazine
@ScienceMagazineSep 17
An inherited genetic mutation may increase lung cancer risk among people who have never smoked, according to a new Science study. By tracing the ancestry of people carrying the rare EGFR T790M variant, researchers uncovered a shared genetic legacy extending back hundreds of years and concentrated in the southeastern United States. Learn more in this week’s issue: scim.ag/46q1kUC
An inherited mutation in the EGFR gene (EGFR T790M) increases lung cancer risk. In this illustration, lungs merge with a map of the United States, reflecting the geographic enrichment of the EGFR T790M mutation. By tracing the ancestry of people carrying this mutation, researchers uncovered a shared genetic legacy extending back hundreds of years and concentrated in the southeastern United States. Illustration: Oliver Uberti

ALT An inherited mutation in the EGFR gene (EGFR T790M) increases lung cancer risk. In this illustration, lungs merge with a map of the United States, reflecting the geographic enrichment of the EGFR T790M mutation. By tracing the ancestry of people carrying this mutation, researchers uncovered a shared genetic legacy extending back hundreds of years and concentrated in the southeastern United States. Illustration: Oliver Uberti

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Lida Wang retweeted
Yun S. Song (@yun_s_song) profile picture
Yun S. Song@yun_s_songSep 9
We are thrilled to share that our GPN-Star manuscript is now published and freely available: doi.org/10.1038/s41586-026-1… (1/n)
Predicting genome-wide functional constraints with GPN-Star

Predicting genome-wide functional constraints with GPN-Star

Nature - GPN-Star, a genomic language model with a phylogeny-aware architecture for whole-genome alignment data, is shown to be a scalable and flexible tool for genetic variant effect prediction...

nature.com
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Lida Wang retweeted
Minhui Chen (@chen_cmh) profile picture
Minhui Chen@chen_cmhAug 26
CIGMA is out in Nature — A linear mixed model to unbiasedly characterize cell-type-specific eQTLs. Work advised by @andywdahl and a lot of help from @xinpei_w nature.com/articles/s41586-0…
Cell-type-specific eQTLs underlie the genetic architecture of complex traits

Cell-type-specific eQTLs underlie the genetic architecture of complex traits

Nature - Single-cell RNA-sequencing shows that cell-type-specific expression quantitative trait loci drive much of complex trait heritability, highlighting cell-type-specific gene regulation as key...

nature.com
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Survey data document US visa types and burdens of time, cost and mental health among international postdocs nature.com/articles/s41587-0… rdcu.be/fB1tP
The invisible tax of US visa bureaucracy on international scholars

The invisible tax of US visa bureaucracy on international scholars

Nature Biotechnology - Survey data document US visa types and burdens of time, cost and mental health among international postdocs.

nature.com
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Lida Wang retweeted
Jian Yang (@jyang1981) profile picture
Jian Yang@jyang1981Aug 5
Postdoc and research scientist positions available in my lab: yanglab.westlake.edu.cn/jobs…
Image from Jian Yang (@jyang1981)
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Lida Wang retweeted
Sarah Urbut (@tigerstatdoc) profile picture
Sarah Urbut
@tigerstatdocJul 15
One of my first consults as a cardiology fellow: a 34-year-old, textbook MI. A day earlier, no risk model would have flagged him for prevention. That paradox has driven my work ever since — our models miss how disease actually evolves, dynamically, on top of a genetic background. @Nature nature.com/articles/s41586-0…
Image from Sarah Urbut (@tigerstatdoc)
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Lida Wang retweeted
Noam Brown (@polynoamial) profile picture
Noam Brown
@polynoamialMay 28
Source: henrikkarlsson.xyz/p/go
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New work from us pooling together clinical sequencing data to identify large effect common risk variants for rare cancer types. This included a novel HLA locus that interacts with HPV infection to increase Anal Cancer risk.
Image from Sasha Gusev (@SashaGusevPosts)
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A little jukebox that plays the top hits from a desired country and year (ordered by most distinct hits for that country).
Image from Sasha Gusev (@SashaGusevPosts)
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Happy to share our new preprint from @SashaGusevPosts and @nmancuso_ labs! We introduce Mr. PEG, a framework integrating perturbational screens, eQTL, and GWAS data to identify mediating genes for complex traits. (1/n) medrxiv.org/content/10.64898…
Integrating perturbational screens, eQTL, and GWAS data identifies mediating genes for complex...

Integrating perturbational screens, eQTL, and GWAS data identifies mediating genes for complex...

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...

medrxiv.org
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Excited to share our new work of regulatory effects in the brain using sc-RNASeq data. Importantly, we argue that besides analyzing single cell eQTLs, it is important to look beyond cell types and better dissect shared and distinct effects between cell types. nature.com/articles/s41467-0…
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How do GWAS and rare variant burden tests rank gene signals? In new work @Nature with Jeff Spence, @jkpritch, and our wonderful coauthors we find the key factors are what we call Specificity, Length, and Luck! 🧬🧪🧵 nature.com/articles/s41586-0…
Specificity, length and luck drive gene rankings in association studies

Specificity, length and luck drive gene rankings in association studies

Nature - Genetic association tests prioritize candidate genes based on different criteria.

nature.com
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The proportion of epistatic heritability that is estimated as additive by quantitative genetic models. Epistasis deviates more from additivity for lower frequency causal alleles, but on average >80% of biological GxG will just look like statistical G.
Image from Sasha Gusev (@SashaGusevPosts)
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Check out our scPrediXcan paper cell.com/cell-genomics/fullt… Led by talented @Charles_Zhou12, supervised by @MengjieChen6 and me, with thanks to many contributors scPrediXcan integrates deep learning and single cell expression data into a powerful cell type specific TWAS framework.
scPrediXcan integrates deep learning methods and single-cell data into a cell-type-specific...

scPrediXcan integrates deep learning methods and single-cell data into a cell-type-specific...

Zhou et al. introduce scPrediXcan, a novel transcriptome-wide association study framework that integrates the deep learning-based model ctPred for cell-type-specific expression prediction. Applied to...

cell.com
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I'm excited to share a wonderful collaboration with @LD_matrix: JOBS integrates bulk and single-cell eQTLs to boost eQTL discovery. Integrated with GWAS, it identified more disease-linked loci for 14 immune disorders & fueled drug-repurposing. #immunology #drugdiscovery #genomics
Dajiang Liu (@dajiangliu81) profile pictureDajiang Liu@dajiangliu8127 Mar 2025
I am excited to share our new work that generates a single cell eQTL atlas for immune cell types. The work integrates bulk eQTLs with sc-eQTLs, which boosts the power for identifying sc-eQTLs for up to 4 folds. As such, we have the power equivalent to sc-RNASeq of 4K individuals.
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Lida Wang retweeted
Xin Ma (@XinMa13) profile picture
Xin Ma@XinMa1318 Mar 2025
🧠🔥"Put on your 3D glasses...oh wait, you don't need them!"😝 Brain Metabolome just got an upgrade-why look at slices when you can see the whole picture in 3D? Check out our latest work in @NatMetabolism .🚀🔬 🔗doi.org/10.1038/s42255-025-0…
Image from Xin Ma (@XinMa13)
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Beyond excited to share this new paper with all of you . It's the most fun we've ever had. We figured out how to study a latent index driving partner choice without measuring it directly🥂 @qinwen_zzz Preprint📰: biorxiv.org/content/10.1101/… Sumstats⬇️: qlu-lab.org/data.html
Image from Qiongshi Lu (@Q_StatGen)
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I am happy to share our new work that predicts the progression of autoimmune diseases, integrating EHR and GWAS datasets @NatureComms . nature.com/articles/s41467-0…
Integrating electronic health records and GWAS summary statistics to predict the progression of...

Integrating electronic health records and GWAS summary statistics to predict the progression of...

Nature Communications - The authors propose a Genetic Progression Score (GPS) model to predict autoimmune disease progression from preclinical stages, integrating genome-wide association study...

nature.com
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Thrilled to share our work to analyze insurance claim datasets to dissect genetic and environmental contributions to 1083 human diseases. We developed a spatial linear mixed model SMILE, using geolocations as a proxy for the environment. nature.com/articles/s41467-0…
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