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September 30, 2025Molecular Ecology ResourcesOpen Access

Assessing Genotype Imputation Methods for Low‐Coverage Sequencing Data in Populations With Differing Relatedness and Inbreeding Levels

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Authors

TVTram ViKSKatarina C. StuartHTHui Zhen Tan

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Overview

Analysis reveals differing imputation accuracy for genetic relatedness and inbreeding levels in populations, impacting results.

Key Points

  • Genotype imputation accuracy varies significantly in populations with low relatedness, affecting overall analysis.
  • Five imputation methods were assessed, including GLIMPSE2 and Beagle5.4, with varying performance across simulated populations.
  • Real population tests confirmed high accuracy in closely related groups, but disparities emerged with distant relatives.
  • The methodology offers a framework for selecting appropriate imputation techniques tailored to specific genetic contexts.

Cite This Study

Vi et al. (2025) studied this question.

synapsesocial.com/papers/68dc261d8a7d58c25ebb2c04https://doi.org/10.1111/1755-0998.70049
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Also Consider

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

  1. 1Benchmarking Imputed Low Coverage Genomes in a Human Population Genetics Context2024 · 2 citations
  2. 2High Imputation Accuracy Can Be Achieved Using a Small Reference Panel in a Natural Population With Low Genetic Diversity.2025 · 1 citations
  3. 3Rapid and accurate genotype imputation from low coverage short read, long read, and cell free DNA sequence2024 · 4 citations
  4. 4Fast and accurate imputation of genotypes from noisy low-coverage sequencing data in bi-parental populations2024
  5. 5Benchmarking for genotyping and imputation using degraded DNA for forensic applications across diverse populations2024 · 1 citations