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August 4, 2025Open Access

Imputation and polygenic score performance of low coverage whole-genome sequencing and genotyping arrays in diverse human populations

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Authors

PNPhuc-Trung NguyenUniversity of FreiburgVNVy NguyenVietnam National University Ho Chi Minh CityDNDat NguyenWrocław University of Science and Technology

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Overview

This analysis compares imputation accuracy and polygenic score performance across genotyping arrays and whole-genome sequencing in diverse populations, highlighting important implications.

Key Points

  • Low coverage whole-genome sequencing performs competitively with genotyping arrays, especially in diverse populations.
  • Results show that low-pass whole-genome sequencing outperforms arrays for rare and low-frequency genetic variants.
  • Data from 2,504 individuals was analyzed using a 10-fold cross-imputation strategy, ensuring robust results.
  • Findings suggest low coverage sequencing is a powerful alternative for large-scale genetic studies in underrepresented groups.

Cite This Study

Nguyen et al. (2025) studied this question.

synapsesocial.com/papers/689a0f8de6551bb0af8d0d9ahttps://doi.org/10.1101/2025.07.18.665609
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Low-pass sequencing increases the power of GWAS and decreases measurement error of polygenic risk scores compared to genotyping arrays2021 · 151 citations
  2. 2Benchmarking Imputed Low Coverage Genomes in a Human Population Genetics Context2024 · 2 citations
  3. 3Boosting the Power of Rare Variant Association Studies by Imputation Using Large-scale Sequencing Population2025 · 3 citations
  4. 4Commonly used genomic arrays may lose information due to imperfect coverage of discovered variants for autism spectrum disorder2024 · 1 citations
  5. 5Assessing Genotype Imputation Methods for Low‐Coverage Sequencing Data in Populations With Differing Relatedness and Inbreeding Levels2025 · 4 citations