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Samuel Pattillo Smith

@sampatsmith.bsky.social
121 followers 118 following 36 posts

Postdoc with @arbelharpak.bsky.social. Popgen and complex traits. All views and opinions are my own. he/him

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Reposted by Samuel Pattillo Smith
Olivia Smith @oliviarxiv.bsky.social · 09/09/2026
Today, we at the @arbelharpak.bsky.social & @docedge.bsky.social labs are excited to share our updated manuscript for PGSUS, a tool for diagnosing confounding in polygenic scores (PGSs).
biorxiv.org
A Litmus Test for Confounding in Polygenic Scores
Polygenic scores (PGSs) are being rapidly adopted for trait prediction in the clinic and beyond. PGSs are often thought of as capturing the direct genetic effect of one's genotype on one's phenotype. ...
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Reposted by Samuel Pattillo Smith
xinyimiao.bsky.social @xinyimiao.bsky.social · 15/05/2026
I am excited to share my first paper, our new preprint: www.biorxiv.org/content/10.6... with @arbelharpak.bsky.social and @docedge.bsky.social. Family GWAS provides direct genetic effect estimates and is increasingly important. But how much can we trust these estimates? (1/15)
biorxiv.org
22514
Reposted by Samuel Pattillo Smith
Jared M. Cole @jmillercole.bsky.social · 14/01/2026
Excited to share our new preprint from the @arbelharpak.bsky.social Lab! How do recruitment into genetic studies and study characteristics impact what we infer about the genetic bases of traits, and what are the consequences? (1/21) www.biorxiv.org/content/10.6...
biorxiv.org
Representation in genetic studies affects inference about genetic architecture
Knowledge of a trait's "genetic architecture," namely the joint distribution of allele frequencies of causal variants and the direction and magnitude of their effects, is essential to understanding it...
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Reposted by Samuel Pattillo Smith
Doc Edge @docedge.bsky.social · 02/11/2024
New work from my lab, led by graduate student Janis Liu. Janis studied type I error rates in Qst/Fst comparisons (1/n) www.biorxiv.org/content/10.1...
biorxiv.org
Error rates in Q_ST--F_ST comparisons depend on genetic architecture and estimation procedures
Genetic and phenotypic variation among populations is one of the fundamental subjects of evolutionary genetics. One question that arises often in data on natural populations is whether differentiation...
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Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
We thank co-authors @oliviarxiv.bsky.social @hakha.bsky.social DanDan Peng and @jeremyjberg.bsky.social; also @gcbias.bsky.social for guidance and advice in developing this approach. Finally, big thanks to some very generous colleagues for their feedback; we’d love to get yours as well! [n/n]
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Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
PGSUS is a demonstration that family-based designs can be useful here: Combining their articulation with the statistical power of population-based designs may pave the way forward in the interpretation and application of genomic predictors. [18/n]
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Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
…given how they integrate many small statistical associations with subtle potential biases. Even now, it feels like we are only scratching the surface! We need tools to better interpret genomic predictors.
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
This preprint is a culmination of over six years of work developing this approach. Following ideas we started developing in Mostafavi, Harpak et al. we became increasingly interested in what is baked into genomic predictors like polygenic scores… [16/n]
elifesciences.org
110
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
We were also able to see that different approaches for adjustment for population structure in GWASs (e.g., PCs as fixed effect covariates, LMMs) have distinct advantages with respect to mitigation of ancestry-axis-specific and isotropic SAD variance in PGS. [15/n]
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Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
In some instances, a given PGS appears to be stratified along a major axis of ancestry in one prediction sample but not in another (for example, in comparisons of prediction in samples from different countries, or in ancient DNA vs.~contemporary samples). [14/n]
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Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[13/n] We also found evidence of stratification and isotropic inflation in PGSs constructed using the UK Biobank.
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Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
Applying PGSUS, we found evidence of stratification in PGSs constructed using large meta-analyses of height and educational attainment. [12/n]
110
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
In particular, PGSUS can detect stratification along major axes of ancestry as well as SAD variance that is “isotropic'' with respect to axes of ancestry. [11/n]
110
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
Our method, Partitioning Genetic Scores Using Siblings (PGSUS, pronounced ``Pegasus''), breaks down variance components further by axes of genetic ancestry, allowing for a nuanced interpretation of SAD effects. github.com/harpak-lab/P... [10/n]
110
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
We leverage a comparison of a PGS of interest based on a standard GWAS with a PGS based on a sibling GWAS---which is largely immune to SAD effects---to quantify the relative contribution of each type of effect to variance in the PGS of interest. [9/n]
110
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
We developed a method that estimates the proportion of variance in a PGS (in a given sample) that is driven by direct effects, SAD effects, and their covariance. [7/n]
110
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
Our interpretation and application of PGSs may hinge on the relative impact of SAD effects, since they may often be environmentally or culturally mediated. [6/n]
111
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
However, because PGSs are constructed from population-level associations, they are influenced by factors other than direct genetic effects, including Stratification, Assortative mating, and Dynastic effects (“SAD effects''). www.science.org/doi/10.1126/... [5/n]
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Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
PGS are often thought of as capturing the direct, causal genetic effect of one's genotype on their phenotype. [4/n]
111
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
Following these observations, attention has turned toward the construction of genomic predictors of traits, so-called “polygenic scores” (PGSs). [3/n]
110
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
GWAS have revealed that the genetic basis of variation for many health conditions and other traits is highly polygenic, and that the joint effect of these variants is often well-captured by a simple linear combination, consistent with longstanding theoretical predictions. [2/n]
cell.com
An Expanded View of Complex Traits: From Polygenic to Omnigenic
Many complex genetic traits arise from large numbers of variants, each with small effects. This Perspective argues that risk is ultimately driven by an even larger number of genes with no direct impac...
110
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
Think of a polygenic score you care about. Are direct genetic effects driving variation among people in this predictor? Or perhaps other, confounding factors? We at the @arbelharpak.bsky.social & @docedge.bsky.social Labs developed a method to tackle this question. [1/n]
biorxiv.org
A Litmus Test for Confounding in Polygenic Scores
Polygenic scores (PGSs) are being rapidly adopted for trait prediction in the clinic and beyond. PGSs are often thought of as capturing the direct genetic effect of one's genotype on their phenotype. ...
27638
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[n/n] We thank @gcbias.bsky.social for guidance and advice in developing this approach. We also thank generous colleagues for their input and feedback; we’d love to get yours as well!
000
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[18/n] PGSUS is a demonstration that family-based designs can be useful here: Combining their articulation with the statistical power of population-based designs may pave the way forward in the interpretation and application of genomic predictors.
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[17/n] ...given how they integrate many small statistical associations with subtle potential biases. Even now, it feels like we are only scratching the surface! We need tools to better interpret genomic predictors.
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[16/n] This preprint is a culmination of over six years of work developing this approach. Following ideas we started developing in Mostafavi, Harpak et al. we became increasingly interested in what is baked into genomic predictors like polygenic scores... elifesciences.org/articles/483...
elifesciences.org
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[14/n] In some instances, a given PGS appears to be stratified along a major axis of ancestry in one prediction sample but not in another (for example, in comparisons of prediction in samples from different countries, or in ancient DNA vs.~contemporary samples).
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[14/n] In some instances, a given PGS appears to be stratified along a major axis of ancestry in one prediction sample but not in another (for example, in comparisons of prediction in samples from different countries, or in ancient DNA vs.~contemporary samples).
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[13/n] We also found evidence of stratification and isotropic inflation in PGSs constructed using the UK Biobank.
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[12/n] Applying PGSUS, we found evidence of stratification in PGSs constructed using large meta-analyses of height and educational attainment.
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[11/n] In particular, PGSUS can detect stratification along major axes of ancestry as well as SAD variance that is “isotropic'' with respect to axes of ancestry.
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[10/n] Our method, Partitioning Genetic Scores Using Siblings (PGSUS, pronounced ``Pegasus''), breaks down variance components further by axes of genetic ancestry, allowing for a nuanced interpretation of SAD effects. github.com/harpak-lab/P...
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[9/n] We leverage a comparison of a PGS of interest based on a standard GWAS with a PGS based on a sibling GWAS---which is largely immune to SAD effects---to quantify the relative contribution of each type of effect to variance in the PGS of interest.
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[8/n] We developed a method that estimates the proportion of variance in a PGS (in a given sample) that is driven by direct effects, SAD effects, and their covariance.
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[7/n] Our interpretation and application of PGSs may hinge on the relative impact of SAD effects, since they may often be environmentally or culturally mediated.
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[6/n] However, because PGSs are constructed from population-level associations, they are influenced by factors other than direct genetic effects, including Stratification, Assortative mating, and Dynastic effects (“SAD effects''). www.science.org/doi/10.1126/...
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[5/n] PGS are often thought of as capturing the direct, causal genetic effect of one's genotype on their phenotype.
110
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[4/n] Following these observations, attention has turned toward the construction of genomic predictors of traits, so-called “polygenic scores” (PGSs).
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[3/n] GWAS have revealed that the genetic basis of variation for many health conditions and other traits is highly polygenic, and that the joint effect of these variants is often well-captured by a simple linear combination, consistent with longstanding theoretical predictions.
cell.com
An Expanded View of Complex Traits: From Polygenic to Omnigenic
Many complex genetic traits arise from large numbers of variants, each with small effects. This Perspective argues that risk is ultimately driven by an even larger number of genes with no direct impac...
100
Samuel Pattillo Smith @sampatsmith.bsky.social · 04/02/2025
[2/n] My colleagues at the @arbelharpak.bsky.social and @docedge.bsky.social labs and I developed a statistical method that breaks down this variation, which we hope will aid in interpretation and application. @oliviarxiv.bsky.social @hakha.bsky.social DanDan Peng @jeremyjberg.bsky.social
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