Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
September 21, 2025Genomics Proteomics & BioinformaticsOpen Access

Boosting the Power of Rare Variant Association Studies by Imputation Using Large-scale Sequencing Population

View Full Paper
Ask AI
Bookmark
Share

Authors

JDJinglan DaiYZY. ZhangYGYuan Gao

Discussion

Loading...

Member takes

Overview

This analysis evaluates the efficiency of imputed data in rare variant studies, suggesting enhanced power for GWAS through large-scale sequencing.

Key Points

  • Using imputed data from large-scale sequencing improves the identification of rare variants in complex traits.
  • TOPMed-imputed data showed a 27.71% increase in identified rare variants compared to conventional methods.
  • Association tests on 45 traits revealed that imputed data from TOPMed aligns closely with whole-genome sequencing findings.
  • Incorporating imputed data enhances the power of rare variant association studies, particularly in limited sample sizes.

Cite This Study

Dai et al. (2025) studied this question.

synapsesocial.com/papers/68d46fd431b076d99fa6a21fhttps://doi.org/10.1093/gpbjnl/qzaf084
View Full Paper
Ask AI
Bookmark
Share

Also Consider

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

  1. 1Yield of genetic association signals from genomes, exomes and imputation in the UK Biobank2024 · 25 citations
  2. 2Accurate cross-platform GWAS analysis via two-stage imputation2024
  3. 3Imputation and polygenic score performance of low coverage whole-genome sequencing and genotyping arrays in diverse human populations2025 · 1 citations
  4. 4UK Biobank whole-genome sequencing reveals robust contributions of rare variants to complex-trait heritability2026
  5. 5Low-pass sequencing increases the power of GWAS and decreases measurement error of polygenic risk scores compared to genotyping arrays2021 · 150 citations