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Base by Base
Gustavo Barra
191 episodes
2 days ago
Base by Base explores advances in genetics and genomics, with a focus on gene-disease associations, variant interpretation, protein structure, and insights from exome and genome sequencing. Each episode breaks down key studies and their clinical relevance—one base at a time. Powered by AI, Base by Base offers a new way to learn on the go. Special thanks to authors who publish under CC BY 4.0, making open-access science faster to share and easier to explore.
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Life Sciences
Health & Fitness,
Medicine,
Science
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All content for Base by Base is the property of Gustavo Barra and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Base by Base explores advances in genetics and genomics, with a focus on gene-disease associations, variant interpretation, protein structure, and insights from exome and genome sequencing. Each episode breaks down key studies and their clinical relevance—one base at a time. Powered by AI, Base by Base offers a new way to learn on the go. Special thanks to authors who publish under CC BY 4.0, making open-access science faster to share and easier to explore.
Show more...
Life Sciences
Health & Fitness,
Medicine,
Science
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180: Leveraging Global Genetics Resources for Equitable Polygenic Prediction
Base by Base
22 minutes 11 seconds
1 week ago
180: Leveraging Global Genetics Resources for Equitable Polygenic Prediction
️ Episode 180: Leveraging Global Genetics Resources for Equitable Polygenic Prediction In this episode of PaperCast Base by Base, we explore how multi-ancestry genome-wide association study resources and modern polygenic score methodologies can improve prediction accuracy across African, East Asian, and European populations, with a focus on practical, computationally efficient strategies that work even when individual-level data are unavailable. Study Highlights:This article systematically benchmarks leading single-source and multi-source polygenic score methods across 10 complex traits using GWAS summary statistics from Ugandan Genome Resource, Biobank Japan, UK Biobank, and the Million Veteran Program. The authors show that combining ancestry-aligned and European GWAS improves prediction in non-European targets and that independently optimized multi-source approaches often outperform jointly optimized methods while being far more computationally efficient. They introduce a generalizable use of the LEOPARD framework to estimate optimal linear combinations of population-specific scores using only summary statistics, achieving performance comparable to individual-level tuning in many settings. All methods are implemented in the GenoPred pipeline, providing an accessible, reference-standardized workflow for equitable polygenic prediction across diverse populations. Conclusion:Multi-source, summary-statistics–friendly approaches implemented in GenoPred offer a practical path to more accurate and equitable polygenic prediction, particularly when leveraging diverse GWAS resources and efficient tuning frameworks like LEOPARD. Reference:Pain O. Leveraging global genetics resources to enhance polygenic prediction across ancestrally diverse populations. Human Genetics and Genomics Advances. 2025;6:100482. https://doi.org/10.1016/j.xhgg.2025.100482 License:This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support:If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/
Base by Base
Base by Base explores advances in genetics and genomics, with a focus on gene-disease associations, variant interpretation, protein structure, and insights from exome and genome sequencing. Each episode breaks down key studies and their clinical relevance—one base at a time. Powered by AI, Base by Base offers a new way to learn on the go. Special thanks to authors who publish under CC BY 4.0, making open-access science faster to share and easier to explore.