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Reposted by Elizabeth Atkinson

From the Labs at Baylor College of Medicine @bcmfromthelabs.bsky.social · 3d

Texas Children's/Baylor College of Medicine Researchers Create Groundbreaking Tool to Improve Accuracy of #GeneticTesting @egatkinson.bsky.social @bcmgenetics.bsky.social @bcmhouston.bsky.social #TCHResearchNews #TexasChildrens @natcomms.nature.com tinyurl.com/jj6kyrrv

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Elizabeth Atkinson @egatkinson.bsky.social · 2d

Thrilled to share our new @natcomms.nature.com paper on local ancestry informed allele frequencies in gnomAD, which are live now on the browser! Check out my stellar PhD student @pragskore.bsky.social’s Bluetorial on how this brings finer detail to variant interpretation 🧬🖥️

Pragati Kore @pragskore.bsky.social · 2d

📃 We’re excited to share our latest work, now published in Nature Communications — a major update to the Genome Aggregation Database (gnomAD) that improves allele frequency resolution for two gnomAD-defined genetic ancestry groups using local ancestry inference (LAI).

Improved allele frequencies in gnomAD through local ancestry inference - Nature Communications

This study incorporates local ancestry into the Genome Aggregation Database (gnomAD) to improve allele frequency estimates for admixed populations, enhancing variant interpretation and enabling more accurate and equitable genomic research and clinical care.

www.nature.com

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Reposted by Elizabeth Atkinson

Konrad @konradjk.bsky.social · 20d

A project many years in the process, we’re pleased to present our work on multi-ancestry meta-analysis across a boatload of traits in the UK Biobank: www.nature.com/articles/s41...

Pan-UK Biobank genome-wide association analyses enhance discovery and resolution of ancestry-enriched effects - Nature Genetics

Genome-wide analyses for 7,266 traits leveraging data from several genetic ancestry groups in UK Biobank identify new associations and enhance resources for interpreting risk variants across diverse p...

www.nature.com

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Elizabeth Atkinson @egatkinson.bsky.social · 26d

Delighted to amplify my talented PhD student’s work! Check it out for a great way to streamline and harmonize Tractor analyses.

nirav-shah.bsky.social @nirav-shah.bsky.social · Sep 8

🚨 New preprint! Traditional GWAS often exclude admixed individuals, missing ancestry-enriched genetic signals. We built Tractor Nextflow Workflow - a modular, scalable pipeline that automates phasing, LAI, and Tractor GWAS, alongside comprehensive documentation.
Preprint: doi.org/10.1101/2025...

Tractor Workflow Pipeline: A Scalable Nextflow Framework for Local Ancestry-Aware Genome-Wide Association Studies

The routine exclusion of admixed individuals from traditional Genome-Wide Association Studies (GWAS) due to concerns about spurious associations has hindered genetic analyses involving multiple ancest...

www.biorxiv.org

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Elizabeth Atkinson @egatkinson.bsky.social · Jul 23

Thanks for the interest! The tutorial code is available to download as supplemental information of the paper, and has been deposited as a community workspace in the All of Us Researcher Workbench.

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Elizabeth Atkinson @egatkinson.bsky.social · Jul 22

In summary, we present a replicable training model that empowers early-career researchers - including and especially those new to computational genomics - to responsibly leverage large-scale biobank data into their research programs and teaching.

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Elizabeth Atkinson @egatkinson.bsky.social · Jul 22

From years 1–3, training outcomes reported by scholars to stem directly from this training included:
📊 17 conference presentations
🔬 Multiple funded research grants
🎓 Numerous genomics modules added in undergrad courses
🤝 Sustained collaborations across institutions

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Elizabeth Atkinson @egatkinson.bsky.social · Jul 22

During the summit, scholars used real short-read WGS data to:
• Prepare phenotypes & covariates
• Run GWAS via Hail
• Visualize results with PCA, Manhattan & QQ plots
• Manage compute costs
All in ~4 hours with no prior coding required.

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Elizabeth Atkinson @egatkinson.bsky.social · Jul 22

Our training was part of the All of Us Biomedical Researcher Scholars Program through @bcmgenetics.bsky.social focused on mentoring early-stage faculty in genomic data science. The curriculum launches with an intensive Faculty Summit, where scholars get hands-on experience working with genomic data.

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Elizabeth Atkinson @egatkinson.bsky.social · Jul 22

Access to big genomic data is growing, but parallel access to skills needed to use it hasn’t kept up.
We created an accessible, cloud-based genomic analysis training bootcamp using real All of Us data, Jupyter notebooks, and the Hail framework to lower the barrier for early-career researchers.

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Elizabeth Atkinson @egatkinson.bsky.social · Jul 22

🚨 New perspective piece in @ajhgnews.bsky.social! 🚨
We developed a hands-on training resource for large-scale genomic data analysis in the All of Us Researcher Workbench, now published here:

The American Journal of Human Genetics @ajhgnews.bsky.social · Jul 22

📣Online now!
📄Implementing a training resource for large-scale genomic data analysis in the All of Us Researcher Workbench
🧑‍💻 @jasminebakerphd.bsky.social @egatkinson.bsky.social & co

Implementing a training resource for large-scale genomic data analysis in the All of Us Researcher Workbench

Baker et al. present a cloud-based training program using the All of Us Researcher Workbench to teach large-scale genomic data analysis. Early-career researchers gained hands-on experience in GWASs, q...

www.cell.com

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Elizabeth Atkinson @egatkinson.bsky.social · Jun 9

Tractor-Mix builds on Tractor’s strengths to detect ancestry-enriched signals while adding power and robust false-positive control for relatedness via a GRM. By modeling both admixture and relatedness, it overcomes key GWAS barriers and enables more accurate, representative genomic discovery.

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Elizabeth Atkinson @egatkinson.bsky.social · Jun 9

Tractor-Mix uses ancestry-specific genotypes as predictors, outputting ancestry-specific effect sizes and P values. We benchmark our new tool in simulations and apply it to multiple admixed cohorts (including UKBiobank and Mexico City Prospective Study), uncovering signals missed by standard GWAS.

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Elizabeth Atkinson @egatkinson.bsky.social · Jun 9

In this work, we introduce Tractor-Mix, a new GWAS method that extends Tractor to handle related admixed samples. It combines a mixed model framework (like GMMAT) with local ancestry-aware genotypes (like Tractor) in a 2 d.o.f. test.

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Elizabeth Atkinson @egatkinson.bsky.social · Jun 9

As biobanks and global cohorts grow, so does the inclusion of admixed individuals with close or cryptic relatedness. This introduces the statistical challenge of two interwoven sources of stratification: admixture and relatedness, which are rarely handled together.

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Elizabeth Atkinson @egatkinson.bsky.social · Jun 9

We previously developed Tractor, a local ancestry-aware GWAS method that’s been widely used to uncover ancestry-enriched signals and refine genetic architecture in admixed populations. But Tractor (being a GLM) only works on unrelated samples, limiting its use in many real-world datasets.

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Elizabeth Atkinson @egatkinson.bsky.social · Jun 9

We're excited to introduce Tractor-Mix, our new method for GWAS in admixed cohorts with relatedness, led by the fantastic @doubletaotan.bsky.social! Read the full preprint here: www.medrxiv.org/content/10.1...
Thanks to all our amazing collaborators who helped make this work possible!

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Elizabeth Atkinson @egatkinson.bsky.social · Apr 9

Check out my stellar PhD student, Pragati's talk on our work generating local ancestry informed frequency estimates in gnomAD as part of the prestigious Emerging Genomic Scientist Symposium next week! Congrats on being selected for this amazing event!

Human Genetics | Genomic Scientist Fellows | UCLA Medical School

The Emerging Genomic Scientist Fellows Program is a cornerstone of justice, equity, diversity, and inclusion initiatives in the Department of Human Genetics.

medschool.ucla.edu

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Elizabeth Atkinson @egatkinson.bsky.social · Apr 3

I'm delighted to be part of this symposium, put on by University of Pennsylvania Perelman School of Medicine, and led by @bpasaniuc.bsky.social and @sarahtishkoff.bsky.social. See you in a few weeks! upenn.co1.qualtrics.com/jfe/form/SV_...

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Elizabeth Atkinson @egatkinson.bsky.social · Apr 2

👏 Huge thanks to all our amazing LAGC collaborators! Special shoutout to Estela Bruxel and Diego Rovaris for leading this crucial work, and of course @janitzamontalvo.bsky.social and @giustilab.bsky.social for co-founding the LAGC and co-leading alongside myself. 💪

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Elizabeth Atkinson @egatkinson.bsky.social · Apr 2

🔍 Why does this matter?
Most psychiatric GWAS are still Euro-centric, limiting the relevance of genetic findings across populations and ancestries. Latin America’s rich genetic, environmental, and cultural diversity presents a unique opportunity to refine genetic discovery & improve global research

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Elizabeth Atkinson @egatkinson.bsky.social · Apr 2

In this review, we:
🌎 Examine the current state of psychiatric genetic studies in the region
💰 Highlight key challenges in data generation, analysis, & funding
🧬 Showcase emerging opportunities for more representative genomic research
🤝 Call for greater collaboration & investment

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Elizabeth Atkinson @egatkinson.bsky.social · Apr 2

📃 I am excited to share our @naturegenet.bsky.social review paper on the state of psychiatric genetics in Latin America, put forth by the Latin American Genomics Consortium (LAGC)! 🎉

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

Psychiatric genetics in the diverse landscape of Latin American populations - Nature Genetics

Latin America and the Caribbean remain largely underrepresented in psychiatric genetics research. This Review highlights the need for more research in these populations to advance genetic insights and...

www.nature.com

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Elizabeth Atkinson @egatkinson.bsky.social · Mar 20

Check out our preprint for more details!
Huge thanks to All of Us participants & our fantastic team! Let’s continue improving polygenic prediction for all 🔬🧬

https://doi.org/10.1101/2025.0…

Elizabeth Atkinson @egatkinson.bsky.social · Mar 20

7/ Looking ahead:
➡️ As sequencing costs drop, WGS could become standard for PGS.
➡️ More representative reference panels & ancestry-aware methods are crucial for equitable genetic prediction.
➡️ Future work should continue to explore improved LD modeling across populations.

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