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Maggie Steiner

@maggiesteiner.bsky.social
206 followers 343 following 24 posts

PhD Candidate @ UChicago Human Genetics

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Reposted by Maggie Steiner
John Novembre @jnovembre.bsky.social · 05/06/2025
Excited for our publication on how the geographic scale of a sample affects the discovery of rare, deleterious variants to be out this week. With a mix of theory, simulation, and data analysis, we show when samples are narrow vs broad, the number of variants discovered and their frequencies change
pnas.org
PNAS
Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...
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Maggie Steiner @maggiesteiner.bsky.social · 03/06/2025
Thank you!
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Maggie Steiner @maggiesteiner.bsky.social · 03/06/2025
Out today in @pnas.org! www.pnas.org/doi/10.1073/...
pnas.org
PNAS
Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...
12816
Reposted by Maggie Steiner
Jeff Spence @jeffspence.github.io · 17/12/2024
What do GWAS and rare variant burden tests discover, and why? Do these studies find the most IMPORTANT genes? If not, how DO they rank genes? Here we present a surprising result: these studies actually test for SPECIFICITY! A 🧵on what this means... (🧪🧬) www.biorxiv.org/content/10.1...
biorxiv.org
Specificity, length, and luck: How genes are prioritized by rare and common variant association studies
Standard genome-wide association studies (GWAS) and rare variant burden tests are essential tools for identifying trait-relevant genes. Although these methods are conceptually similar, we show by anal...
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Maggie Steiner @maggiesteiner.bsky.social · 05/12/2024
Hi! Could I please be added? Thanks for setting this up!
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Maggie Steiner @maggiesteiner.bsky.social · 05/12/2024
I just figured out how to use feeds! So, sharing this with #popgen 🧪
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Maggie Steiner @maggiesteiner.bsky.social · 05/12/2024
Thanks Erik!
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Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
Thanks to co-lead Dan Rice & co-authors @aabiddanda.bsky.social, Marida Ianni-Ravn, and Chris Porras!
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Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
Overall - while our theoretical model is no doubt a simplification of the complex dispersal/evolutionary processes seen in natural populations, especially humans - we hope that this work will help improve our interpretation of existing genetic studies and provide guidance for the design of new ones.
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Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
Our results have implications for several applications of genetic data. Power to detect trait/disease associations (e.g., GWAS) is tied to allele frequency. The SFS is also used for inference of the distribution of fitness effects, which our results suggest may be biased by effects of study design.
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Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
However, when it comes to avg. allele frequency across all sites (incl. monomorphic ones) these effects can cancel - in our theoretical model we see unchanging avg. allele frequency with sampling design. In human data we see this for fine scale samples (within the UK) but not for broader samples.
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Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
We find evidence of these effects in re-sampling experiments using the UK Biobank. For example, our broadest re-sample with n=10,000 discovers ~98% more variant LoF sites than our most narrow sample, but allele frequency at those variant sites is on average ~41% lower.
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Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
Broad samples will sample a greater number of rare, deleterious variants than narrow samples (we call this “discovery”), but each will be sampled at lower average frequency (we call this “dilution”). These effects lead to substantial changes in some summary statistics, especially for large samples.
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Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
We develop a model for the evolution of carriers of rare deleterious variants, and use it to approximate the site frequency spectrum (SFS, the distribution of allele frequencies) in samples at various scales of geographic breadth. We find several key patterns as samples go from “narrow” to “broad”.
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Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
We focus on rare, deleterious variants, which are expected to cluster in geographic space. Rare variants are also generally of interest since they tend to have large effects on traits (including disease traits), and can help improve understanding of biological mechanisms.
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Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
In particular, we are interested in geographic breadth, or how broad a region across which individuals are sampled. This is important to current discourse in human genetics surrounding the Euro-centric bias of genetic datasets, and the launch of new biobanks to improve representation globally.
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Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
Excited to share a new preprint with @jnovembre.bsky.social ! We use a combination of population genetic theory, simulation, and data analysis to ask: how does study design in genetic studies (including biobanks) impact the discovery of rare, deleterious variants?
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Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
Thanks to co-lead Dan Rice + co-authors @aabiddanda.bsky.social, Marida Ianni-Ravn, and Chris Porras!
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Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
Overall - while our theoretical model is no doubt a simplification of the complex dispersal/evolutionary processes seen in natural populations, especially humans - we hope that this work will help improve our interpretation of existing genetic studies and provide guidance for the design of new ones.
100
Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
Our results have implications for several applications of genetic data. Power to detect trait/disease associations (e.g., GWAS) is tied to allele frequency. The SFS is also used for inference of the distribution of fitness effects, which our results suggest may be biased by effects of study design.
100
Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
However, when it comes to avg. allele frequency across all sites (incl. monomorphic ones) these effects can cancel - in our theoretical model we see unchanging avg. allele frequency with sampling design. In human data we see this for fine scale samples (within the UK) but not for broader samples.
100
Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
We find evidence of these effects in re-sampling experiments using the UK Biobank. For example, our broadest re-sample with n=10,000 discovers ~98% more variant LoF sites than our most narrow sample, but allele frequency at those variant sites is on average ~41% lower.
100
Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
Broad samples will sample a greater number of rare, deleterious variants than narrow samples (we call this discovery), but each will be sampled at lower average frequency (we call this dilution). These effects lead to substantial changes in some summary statistics, especially for large samples.
100
Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
We develop a model for the evolution of carriers of rare deleterious variants, and use it to approximate the site frequency spectrum (SFS, the distribution of allele frequencies) in samples at various scales of geographic breadth. We find several key patterns as samples go from “narrow” to “broad”.
100
Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
We focus on rare, deleterious variants, which are expected to cluster in geographic space. Rare variants are also generally of interest since they tend to have large effects on traits (including disease traits), and can help improve understanding of biological mechanisms.
100
Maggie Steiner @maggiesteiner.bsky.social · 04/12/2024
In particular, we are interested in geographic breadth, or how broad a region across which individuals are sampled. This is important to current discourse in human genetics surrounding the Euro-centric bias of genetic datasets, and the launch of new biobanks to improve representation globally.
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